Acinetobacter baumannii (MDR-AB) isolated on pleural fluid culture, treated with colistin and cefiderocol for about 3 weeks. The molecular research of MDR-AB on transtracheal aspirate was negative following this therapy.We analyzed the case of a 49-year-old woman with HIV infection off-therapy with poor viro-immunological compensation, not vaccinated for SARS-COV-2, hospitalized for lobar pneumonia and severe COVID19-related respiratory failure in intensive care unit (ICU). The hospitalization was complicated by bacteraemic ventilator-associated pneumonia (VAP) caused by multidrug-resistant Acinetobacter baumannii infection in HIV-infected patient.The aim is to show the safety, efficacy and tolerability of colistin-based combination therapy with cefiderocol for   The organism causes outbreaks of infection and health care-associated infections. Antimicrobial resistance greatly limits the therapeutic options, especially if isolates are resistant to the carbapenem class Colistin usually combined to other drugs such as tigecycline, ampicillin/sulbactam, meropenem or fosfomycin has been considered the backbone therapy despite its considerable nephrotoxic effect The burden of CRAB has been increasing during the COVID-19 pandemic; the weakening in antimicrobial resistance surveillance activities, the need for reorganizing ICU spaces and activities during pandemic waves and the overuse of antibiotics for COVID-19 pneumonia contribute to this increase ,5.Data on the efficacy, safety, tolerability of cefiderocol in patients with CRAB infections are still lacking. There are also no studies in this regard applied to patients with HIV infection.The aim of this study is to evaluate the impact of cefiderocol-colistin regimen on the outcome of HIV and COVID-19 infected patient with CRAB infection.249-year-old female patient, drug addict, smoker, with a 27-year history of HIV infection, voluntarily off-therapy for 25 years. Not vaccinated for SARS-CoV-2.Streptococcus pneumoniae-related lobar pneumonia with bilateral interstitial involvement, areas of acute inflammatory hypodiaphania in the right mid-basal site and pleural effusion on the right at chest x-rays.She was hospitalized on April 2022 for respiratory failure due to SARS-CoV-2-pneumonia combined to 3 and CD4-to-CD8 ratio was 0.19.At the time of hospitalization HIV-RNA was 4,545,746 copies/mL, CD4 cell count was 25/mmStreptococcus pneumoniae for 7 days. About SARS-CoV-2-pneumonia steroid-therapy and anticoagulant-prophylaxis were performed. The antigenic nasopharyngeal swab for SARS-CoV-2 became negative after 3 weeks.She started antibiotic therapy with ceftriaxone for Regarding the management of respiratory failure, cycles of high flow oxygen therapy, non-invasive mechanical ventilation and pronation-supination were performed. Orotracheal intubation was executed due to worsening of respiratory exchanges. Eventually, due to difficulty in weaning from mechanical ventilation, percutaneous tracheostomy was prepared, and mechanical ventilation was subsequently disconnected. The patient was transferred to the ordinary ward with supplementation of low oxygen flows via tracheostomy, in spontaneous breathing.Acinetobacter baumannii. The same microorganism was subsequently isolated also on rectal swab and blood cultures from peripheral venous blood. As for susceptibility testing , showing resistance of Acinetobacter to all antibiotic classes but polymyxins  and procalcitonin (PCT) values . Moreover a progressive radiological improvement was observed as shown in There was a progressive improvement in respiratory exchanges until reaching of spontaneous breathing with delivery of low-flow oxygen therapy and the chest drainage was removed. The patient was transferred to the ordinary infectious disease ward, where antibiotic therapy was continued. Molecular research for 3 and CD4-to-CD8 ratio 0.10. After normalization of renal function, the patient resumed antiretroviral therapy using a tenofovir alafenamide fumarate (TAF)/emtricitabine (FTC) + dolutegravir (DTG) regimen.During hospitalization a new viro-immunological determination showed HIV-RNA 2,096,183 copies/mL, CD4 90 cells/mm3CRAB infection has been associated with an increased risk of mortality, particularly in COVID-19 patients with current infection or recent healing Acinetobacter baumannii should be limited to cases where other options are not suitable. Similarly, ESCMID guidelines conditionally recommend against the use of cefiderocol, based on low-certainty evidence. In both Societies'recommendations, ampicillin-sulbactam is suggested as a preferred agent for mild-to-severe infections caused by CRAB, alone or as a part of combination therapy. However, in our Centre, susceptibility test for ampicillin/sulbactam is not available, even if evidence seems to suggest that high-dose ampicillin-sulbactam could still retain a non-negligible clinical efficacy.According to the 2022 IDSA guidance on the treatment of multidrug resistant pathogens, cefiderocol use in the context of infections by Acinetobacter baumannii. Analyzing the epidemiology of CRAB in our hospital, almost all of the circulating Acinetobacter baumannii is a producer of OXA-23 which is not sensitive to therapy with ampicillin/sulbactam. For patients with CRAB resistant to sulbactam, ESCMID 2022 guidelines recommend against high-dose tigecycline. About the use of rifabutin or other rifamycins, ESCMID 2022 and IDSA 2021 guidelines do not recommend polymyxin-rifampin combination therapy. About fosfomycin, IDSA 2021 guidelines does not favor the use of fosfomycin as a component of CRAB therapy.Not all molecules display equivalent activity against A. baumannii although episodes of MIC increases, especially upon monotherapy administration, have been reported during therapy [Among commercially available options, only colistin (if sensitive to antibiogram) and the recently approved cephalosporin, cefiderocol, have shown significant activity against this pathogen. Registration studies of cefiderocol have demonstrated efficacy in severe infections induced by  therapy ,8. The SCRAB represents a true pathogen capable of contributing to excess mortality. It is challenging to determine if poor clinical outcomes are attributable to suboptimal antibiotic therapy or to underlying host factors such as immunocompromise in HIV infection. In this case report we use combination therapy with 2 agents but not among polymyxin plus fosfomycin or tigecycline or ampicillin/sulbactam or meropenem as ESCMID 2022 guidelines and 2022 IDSA guidance suggest. Moreover according to randomized clinical trial (RCT) CREDIBLE we get poor outcomes with cefiderocol as monotherapy in pneumonia and BSI. The 30-day survival of a patient with concomitant Acinetobacter baumannii, SARS-CoV-2 and HIV infection, and the microbiological clearance with colistin-cefiderocol combination therapy is a promising result, which adds new information on the clinical experience with cefiderocol compared to trials and international guidelines.Results from the phase 3 RCT CREDIBLE comparing cefiderocol to the best available therapy in patients with CR-GNB showed an unexpected increase of mortality in the subset of patients with CRAB p < 0.01) Seven RCTs have investigated the role of combination therapy for CRAB infections and only 1 of the 7 trials indicated a potential benefit with combination therapy. Colistin vs. colistin + rifampin: 210 ICU patients with invasive CRAB infections, no difference in 30-day mortality. Higher microbiological cure in the combination arm Acinetobacter baumannii. In addition, we report 3 retrospective cohort studies of critically ill patients with CRAB infections performed at Chiang Mai University Hospital: colistin vs colistin + vancomycin with no significant differences in 30-day mortality, clinical response, microbiological response and the nephrotoxicity rates We discussed above the issue of combining colistin with other drugs for the treatment of MDR Acinetobacter to colistin, the unpredictable pharmacokinetic/pharmacodynamic profile of this drug is a treatment limit. In fact, colistin has been associated with a low concentration in the epithelial lining fluid In this case a combination therapy with colistin and cefiderocol was preferred for this patient with severe deterioration of respiratory status. Despite the favourable minimum inhibitory concentration of Particularly, besides the favorable clinical outcome, it seemed to have led to microbiological cure: in fact, the molecular research of MDR-AB on tracheal aspirate was negative following combination therapy with colistin and cefiderocol in association with the source control of empyema with thoracic drainage. In addition to efficacy, the therapy was also safe and well tolerated.Despite the severity of the clinical picture to which hospitalization in intensive care, VAP, empyema, BSI, HIV-related immunosuppression and concomitant COVID-19 have contributed, with the combined cefiderocol-colistin therapy, therapeutic and microbiological success were achieved.Acinetobacter baumannii and is currently the only b-lactam displaying such activity against this microorganism. None of the novel b-lactamase inhibitors  have demonstrated activity against Acinetobacter oxacillinases, nor activity against metalloenzymes, and as a result, the new combinations do not display any activity against Acinetobacter.Cefiderocol has demonstrated in vitro activity against Acinetobacter baumannii strains, the sensitivity of the A. baumannii to colistin (shown on the susceptibility test) and the immunocompromised state of patient with respiratory deterioration, we can associate colistin (certainly active but with low intrapulmonary penetration) with cefiderocol .Albeit limited, several real-life experiences reporting the use of cefiderocol as monotherapy (concerning the treatment of such infections) in the context of rescue therapy, but combo therapy with colistin doesn't investigate. In clinical centers where ampicillin/sulbactam and cefiderocol susceptibility testing is not available, in consideration of the epidemiology of circulating Acinetobacter baumannii.Our report suggests the potential role of cefiderocol in the treatment of CRAB infection even in HIV infected patients, adding new information on the clinical experience with this drug. Well-designed clinical studies are needed to generalize these findings, allowing for a more defined clinical use of cefiderocol, especially concerning infections by A.C. received support for travel to meetings from ViiV Healthcare, A.B. received speakers’ honoraria from ViiV Healthcare, and fees for attending advisory boards from Janssen-Cilag. S.D.G. was a paid consultant or member of advisory boards for Gilead Sciences, ViiV Healthcare, Janssen-Cilag, Merck Sharp & Dohme and Bristol-Myers Squibb. All other authors: none to declare.


Freezing of gait (FOG) is a common motor symptom in advanced Parkinson’s disease (PD). However, the pathophysiology mechanism of FOG is not fully understood. The purpose of this study was to investigate microstructural abnormalities in subcortical gray matter and alterations in functional connectivity of the nuclei with microstructural changes. In addition, the correlations between these microstructural and functional changes and the severity of FOG were measured.Twenty-four patients with FOG (PD-FOG), 22 PD patients without FOG (PD-nFOG), and 27 healthy controls (HC) were recruited. FOG Questionnaire (FOGQ) and Gait and Falling Questionnaire (GFQ) were assessed, and Timed Up and Go (TUG) tests were performed in PD-FOG patients. All subjects underwent diffusion tensor imaging (DTI) and resting-state functional MRI scanning. The DTI measures, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), were extracted and measured from basal ganglia, thalamus, and substantia nigra. The nuclei with microstructural alterations were selected as seed regions to perform the seed-based resting-state functional connectivity.The MD and RD values of the right globus pallidus internus (GPi) were significantly higher in patients with PD-FOG compared with PD-nFOG patients and HC. In PD-FOG patients, the MD and RD values of the right GPi were significantly correlated with the time of the TUG test in both ON and OFF states. The MD values were also correlated with the GFQ scores in PD-FOG patients. Resting-state functional connectivity between the right GPi and left middle occipital gyri decreased significantly in PD-FOG patients compared to PD-nFOG patients, and was negatively correlated with GFQ scores as well as the time of ON state TUG in PD-FOG patients.Microstructural alterations in the right GPi and functional connectivity between the right GPi and visual cortex may be associated with the pathophysiological mechanisms of FOG in PD patients. Freezing of gait (FOG), a common motor symptom in Parkinson’s disease (PD), is described as a momentary, episodic absence or marked reduction of forwarding movement of the feet despite the intention to walk . It is aMultiple brain regions in the basal ganglia circuit have been suggested to be associated with FOG in PD . Of thesDespite several studies confirming the presence of functional alterations of GPi in PD-FOG, a limited number of studies have concentrated on the microstructural differences between PD-FOG and PD patients without FOG (PD-nFOG). The microstructure can be sensitively quantified using diffusion tensor imaging (DTI), by detecting altered diffusion patterns of water molecules in brain tissue . Higher Several nuclei have been used as predefined seeds, for instance, pedunculopontine, thalamus, and dentate nucleus for seed-based resting-state functional connectivity (rs-FC) analysis, and observed that their FCs were altered in PD-FOG patients . NetworkIn the current study, we used the region of interest (ROI)-based DTI technique to explore the microstructure of nuclei in the basal ganglia circuit, including the bilateral caudate, putamen, GPi, globus pallidus externa (GPe), thalamus, and substantia nigra (SN)  were recruited from the Department of Neurology, Beijing Tiantan Hospital, Capital Medical University from April 2021 to December 2021. The diagnosis of PD was according to the Movement Disorder Society Clinical Diagnostic Criteria for PD . Twenty-Demographic details including age, gender, and educational years were obtained. The MMSE and Frontal Assessment Battery (FAB)  were acqThe severity of FOG was evaluated using the FOGQ  and GaitNeuroimaging was acquired on a 3-Tesla magnetic resonance (MR) scanner  using a 48-channel-phased array head coil. Scanning was performed during the OFF state for the patients. All subjects were instructed to keep their heads still and eyes open during scanning, but not to think or fall asleep.2 and three b = 0 images); T2*-weighted blood oxygen level-dependent (BOLD) sequence was carried out for the resting state measurement . Both DTI and BOLD sequences were carried-out with the multiband accelerated echo planar imaging (EPI), with the new ARC acquisition pattern.Magnetic resonance protocol included the following sequences: 3D T1-weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence ; DTI sequence , mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were generated by applying the dtifit tool.FMRIB Software Library tools3  152 standard space, and the invwarp tool was used to calculate the inverse transformation of T1 maps to standard space. Both inverse transformations were combined by using the convertwarp tool. For each participant, the applywarp tool was further used to co-register standard space ROI masks to the subject space. To verify the accuracy of placement, the ROI masks in the subject’s space were overlayed on each subject’s DTI map. Two PD-FOG patients were removed for poor registration. The mean MD, RD, AD, and FA values within the ROIs were obtained by the fslstats tool  or 3°(rotation). Data from one HC subject and two PD-FOG subjects were excluded from the analysis due to excessive head movement. The images were normalized to the MNI152 standard space of 3 × 3 × 3 mm3. The effect of six head movement measures, as well as white matter and cerebrospinal fluid signals, was removed using linear regression. Then the images were spatially smoothed using a Gaussian kernel with a 6-mm full width at half maximum. Next, the data were linearly detrended and temporally bandpass filtered at a low frequency (0.01–0.08 Hz). Nuclei with microstructural alterations in the PD-FOG group compared with both the PD-nFOG and HC groups were used as seed regions. The seed-based resting-state functional connectivity (rs-FC) was performed using Pearson correlations. Then the correlation coefficients were calculated by Fisher’s Z transformation.Resting-state functional MRI (rs-fMRI) datasets were pre-processed using RESTplusV1.2p < 0.05. Shapiro-Wilk test was performed for demographic and clinical data distribution. The detailed p-values for the Shapiro-Wilk test are shown in Statistical analyses of demographic, clinical, and gait assessments were performed in SPSS25. The significant level was set to p < 0.01, clusters AlphaSim corrected p < 0.05). To determine between-group rs-FC differences, independent two-sample t-test was further performed within a mask showing significant differences among the three groups .Statistical analysis of the functional MRI data was performed using SPM12. Voxel-wise differences among PD-FOG, PD-nFOG, and HC groups were carried out using one-way ANOVA , 22 in the PD-nFOG group , and 27 in the HC group . There was no significant difference in age, gender, educational years, and MMSE score among the three groups . No signF = 5.203, p = 0.008; RD, F = 6.652, p = 0.002). Pairwise comparisons showed that the MD value was significantly higher in patients with PD-FOG compared to PD-nFOG (p = 0.041) and HC groups  and HC . The AD value of the right SN was significantly higher in patients with PD-FOG compared with the HC group . Pairwise comparisons showed that the FA value of the right caudate was significantly higher in patients with PD-nFOG patients compared to HC  of bilateral caudate, GPe, GPi, putamen, thalamus, and SN are shown in r = 0.451, p = 0.040), and times of OFF state TUG  and ON state TUG  in the PD-FOG group  as well as ON state TUG  in the PD-FOG group  serve as output nuclei of the basal ganglia and provide inhibitory afferent connections to the pedunculopontine nucleus (PPN) and thalamus that control gait (Globus pallidus internus is a crucial component of the neural network that is closely linked with FOG. It has been observed that the GPi and substantia nigra rol gait . The “crrol gait . In linerol gait .From a network perspective, we found a decreased FC between the GPi and the visual cortex in PD-FOG patients compared with PD-nFOG patients. Motor-visual information transfer plays important role in motor control. It has been demonstrated that visual functional deficit impacted gait impairment in PD . InteresNotably, the current study showed alterations mainly in the right hemisphere of PD-FOG patients, which is consistent with a growing body of literature demonstrating that the right hemisphere appears to be selectively affected in FOG . The latThere are some inconsistencies between our observation and previous DTI studies investigating subcortical microstructure change in PD-FOG. There are some limitations in our study. The present case-control study does not reflect longitudinal alterations in microstructure and FC. In our future study, the collection of follow-up data would provide more valuable information about longitudinal alterations in microstructure and FC. Besides, the relationship between the laterality of FOG and asymmetry of imaging alterations should be investigated. In addition, our relatively small sample size restricted the generalizability of the results and prevented us from performing a study of subtypes of FOG. Further large-sample, multicenter studies are required to confirm the generalizability of the results and investigate the distinct mechanisms between the subtypes of FOG in Parkinson’s disease.In conclusion, the microstructural abnormalities of the right GPi were observed in PD-FOG patients and were positively associated with the gait measures. The FC between the right GPi and visual cortex was reduced in PD-FOG patients, compared with PD-nFOG patients, and was negatively related to the gait measures as well. Our findings suggest that microstructural alterations in the right GPi and reduced FC between the right GPi and visual cortex maybe associated with the pathological mechanism of FOG in PD patients.The original contributions presented in this study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee of Beijing Tiantan Hospital, Capital Medical University, Beijing, China. The patients/participants provided their written informed consent to participate in this study.TF and WK designed the study. WK, XW, YZ, JZ, and HHC contributed to data collection and data analysis. WK and XW drafted the manuscript. TF, BS, and HMC revised the manuscript. All authors contributed to the article and approved the submitted version.


BEER’ requirement, i.e., biocompatibility, electrical elasticity, and robustness, is first proposed here for all the on-skin healthcare electronics for epidermal applications. This requirement would guide the designing of the next-generation on-skin healthcare electronics. For conventional stretchable electronics, the rigid conductive materials, e.g., gold nanoparticles and silver nanofibers, would suffer from an easy-to-fail interface with elastic substrates due to a Young’s modulus mismatch. Liquid metal (LM) with high conductivity and stretchability has emerged as a promising solution for robust stretchable epidermal electronics. In addition, the fundamental physical, chemical, and biocompatible properties of LM are illustrated. Furthermore, the fabrication strategies of LM are outlined for pure LM, LM composites, and LM circuits based on the surface tension control. Five dominant epidermal healthcare applications of LM are illustrated, including electrodes, interconnectors, mechanical sensors, thermal management, and biomedical and sustainable applications. Finally, the key challenges and perspectives of LM are identified for the future research vision.Wearable devices are receiving growing interest in modern technologies for realizing multiple on-skin purposes, including flexible display, flexible e-textiles, and, most importantly, flexible epidermal healthcare. A ‘ Wearable devices are of paramount importance for human life in such an era of everything being interconnected, smart, and intelligent ,2,3,4. IBEER’ requirement. 1. Biocompatibility: Biological compatibility is most significant for on-skin applications, especially for in vivo and in vitro biotoxicity. The conductive materials should be nontoxic to ensure the safety of the epidermal system. In addition, air-permeability and thermal comfort are important to prevent skin lesions and inflammation while ensuring long-term comfortable wearing. 2. Electrical elasticity: The conductive materials should be designed with satisfying strain tolerance to maintain their functions in on-skin scenarios. In more detail, the conductors should show stable conductivity under stretching and recovering. 3. Robustness: The epidermal system provides a dynamic deformation scenario for on-skin conductive materials. Under long-term dynamic stretching, bending, and twisting, the conductors or electrodes are supposed to maintain their conductivity for long-term use, and the biosensors should present robust sensitivity.For conductive materials on the epidermal system , three bBEER’ requirement, a series of conductive materials and devices are being proposed and developed to constitute a smart wearable healthcare monitoring system . T. T2O3) fid metal J 52]. A. A2O3) fDue to their high biocompatibility, typical low-melting alloys that contain Ga, In, Sn, and Bi elements have been used in a variety of biomedical and health technologies . Among tAs new-generation functional materials, low-melting liquid metal preparations are becoming increasingly significant. For stretchable electronics, liquid metals or their alloys provide a superior alternative for conductive and functional components due to their high conductivity and excellent fluidity. The high surface tension of alloys and their poor wettability with many substrates severely restrict the patterning of LMs, and for the mass production of LM-based electronics, there are still a lot of problems that need to be overcome, especially in the most-adopted printing technology. To create acceptable functional materials based on gallium or its alloys, numerous techniques have been developed, including microfluidics, surface modification, lowering surface tension via the additions of metals or elastomer materials, and printing. The application range of the low-melting liquid metals has been further enlarged to accommodate varied needs thanks to these technologies, which have not only allowed for the modification of their physical properties but also introduced a variety of new functionalities. This chapter summarizes the fabrication methods of functional LM materials for stretchable electronics.Printing or injecting pure LM into a channel with a certain shape to create a functional circuit is a common technique for creating liquid metal microfluidic electronics. The atomically thin layer of liquid metal oxides exposed in the air can support a maximum surface stress of 0.5–0.6 N/m . Boley eLM microchannels can be created in two-dimensional platforms by injecting liquid metal into prefabricated channels. Dickey et al. discovered that EGaIn presents the properties of elastic materials until applied with ~0.5 N/m surface stress, at which point the EGaIn can be pressed quickly (within 1s) to fill the channels. For microfluidic channels, a larger critical surface stress would be required, i.e., ~0.6 N/m, which is remarkably similar to the surface tension of EGaIn . Figure Micro- and nano-sized LM droplets are fabricated to realize easier access to the application of LM . The sizSimple mechanical stirring or blending with other functional materials can likewise distribute liquid metal bulks into liquid metal micro–nano droplets. Low melting point metal alloys are mechanically stirred under fluid flow to produce tiny particles C 42]. B. B42]. BThe atomization of LM enables its applications in patterning on multi-substrates via spray deposition. In addition, a straightforward ultrasonication method in the presence of organic solvents may be used to turn LM into nanoparticles to produce numerous functionalities. The walls of a Petri dish are struck by LM during the process of ultrasound. This dispersion is mostly caused by the considerable energy that the LM gained during the collision with the wall. When the surface tension of LM is unable to contain the energy, the LM droplets break down into smaller nanoparticles to decrease the energy. Most of this ultrasonic dispersion occurs in liquid environments where emulsifiers are present. As seen in In the meantime, the surface oxidation layer of LM serves as an ideal stage for the functionalization and polymerization of the LM nanoparticles . Thiolat2O3 layer and distributed in the LM , exhibit low viscosity and are easily processible as well . Furthern, as in   introduction is the key to enabling the interactions with the Gae the LM . Hydrogee the LM  /radio frequency identification devices (RFID), and interconnectors with a PCB board. To reduce the surface tension and improve the wettability for more processibility, a nickel and EGaIn mixture was developed to be printed as an electronic tattoo on human skin C in 104104. WhenMoreover, an LM-fiber-based textile electronic system was designed for near-field powering and communication , where LThrough the structure design of LM-based electronics, mechanical sensors can be fabricated based on the mechanisms of capacity, resistance, piezoelectricity, triboelectricity, etc. When fabricated as a capacitive sensor, LM could serve as the electrode with high conductivity or the diametric layer with a non-conductive and high-dielectric constant. An LM-based highly robust electrode was fabricated with electrospinning and electrospray, after which a capacitive sensor array, named an adaptive human–machine interactive system, was designed via the particle activation of the original composite A in 74]74]. This−1 and be used for the real-time measurement of carotid arterial pressures.Resistance-based sensors are also preferred for epidermal sensing among LM-based electronics . The strMechanical sensors based on other mechanisms, such as electromagnetic induction, electrical induction, triboelectricity, and piezoconductivity, were also applied in flexible on-skin healthcare, where the LM mainly serves as a conductive element. A liquid metal spiral coil was developed to harvest electrical energy under a permanent magnetic field, forming a self-powered stretchable sensor A in 109109. WhenIn addition, electromagnetic interference shielding effectiveness (SE) is a significant parameter for electromagnetic pollution prevention. A multifunctional electromagnetic film was developed with a magnetic LM droplet-filled elastomer C in 111111. UponTriboelectric nanogenerators and sensors are based on the contact electrification and electrostatic induction effect . A stainThe mechanism of positive piezoconductivity for LM-based composites was proposed through an LM-filled magnetorheological elastomer, which consists of LM microdroplets and magnetic microparticles E in 89]89]. It iOther novel structure designs of LM components pave pathways for the detection of algesthesia by taking advantage of its fluidity and self-healing properties . More im−1 K−1, respectively. This unique characteristic of thermal conductivity difference shows its potential for on-body thermal management textiles or energy-saving buildings.Thermal management is becoming increasingly important to meet the basic requirement of human thermal comfort and other medical healthcare strategies . For on-Continuous thermal therapy and warmth retention are the most common strategies for the applications of conformal and conductive composites on skin based on joule heating . LM-baseOther aspects of LM-based applications that are important in epidermal healthcare electronics have also been explored, including biosensing and energy supplying, epidermal micro-environment care, and epidermal protection . A silver–LM island–bridge structure was constructed with the advantages of both mechanical and electrical resiliency under dynamic deformations A in 117117. This2O, Cu, and CuGa2. Coated with LMCu, the fabrics displayed broad-spectrum efficacy against Gram-positive and Gram-negative bacterium, fungi, and respiratory RNA human viruses.In addition, the wound healing and anti-microbial applications for epidermal protection are significant, especially in the post-pandemic era (COVID-19). An LM-based wet-adhesive electronics that can conformally adhere to the skin during a 48-hour wearing period with sports and showers B was conIn addition, the increasing electronic waste has gained considerable attention and urgent requirements for recyclable, degradable electronics . LM possThe gas permeability of LM-based epidermal electronics is of significance for on-skin moisture comfort for long-term applications. Although LM is an intrinsically impenetrable barrier for gases (air and water vapor), porous LM conductive networks have been developed with textile or scaffold structures. An LM fiber mat was fabricated to achieve high permeability and stretchability via a pre-stretching process to a strain of 1800% E in 57]57]. In tBEER’ requirement, i.e., biocompatibility, electrical elasticity, and robustness, is proposed in this review and for the guidance of future epidermal devices and systems. Before the discussion of the fabrication strategies of LM, the fundamental physical, chemical, and biocompatible properties of LM were thoroughly discussed. Consequently, four dominant LM strategies for the fabrication of LM electronics through size effect and surface reduction processes were comprehensively illustrated. Through these methodologies and technologies, a variety of on-skin healthcare applications of LM-based electronics was exhaustively discussed in five parts, i.e., electrodes for biomedical signal collections, interconnectors for functional circuits, mechanical sensors with various mechanisms, thermal management, and other biomedical sustainable applications. Although landmark progress has been achieved and widespread applications have been explored in epidermal healthcare, there are still several bottleneck challenges that limit the further development of LM-based electronics. Here, we list some major challenges and potential solutions as follows:Leakage and encapsulation: Without the protection of an elastomer sheath or encapsulation, the leakage of LM would easily occur in deformations or under pressure. This has been a tricky issue in the practical application of LM-based electronics for a long time, especially for epidermal uses. Although the Ga-based LM was proved to be low cytotoxic, the residual LM after use and the leakage during dynamic deformations would affect the electrical resistance of the circuit or cause a short circuit. There are three main strategies for the leakage inhibition of LM, i.e., encapsulation, structure design, and size effect. The most common way to prevent the leakage of LM is based on physical encapsulation with elastomers. The encapsulation layers serve in the form of a condensed elastomer film , electroxOy particles as well as internal air holes [xOy components, Ga and In atoms through SEM, X-ray photoelectron spectroscopy (XPS), and energy-dispersive spectrometry (EDS). The potential solutions would go alongside other advanced characterization methodologies, including molecular dynamics simulation, atom probe tomography, etc.The mechanism of the modification of low viscosity LM: As discussed above, one of the effective methods for the surface tension reduction of LM is the mixture of LM and other rigid metal particles, including iron, copper, and nickel. The schematic model of the composites’ microstructure was provided to illustrate how the additive metal particles were wrapped with the gallium oxidation layer in . In addiir holes . HoweverThe robust interfaces between LM-based circuits and semiconductor chips: Interconnection plays a significant role in robust on-skin electronics, and the interconnection enhancement between an LM and commercial semiconductor chips could definitely promote the development of hybrid electronics that could be potential candidates for high-density, multifunctional, and smart on-skin electronics. The current strategies involve developing intrinsically sticky conductors by compositing LM particles and adhesive elastomer ,127. LM-The package of the whole epidermal healthcare system: LM-based electronics present tremendous potential in preventative medicine in the post-pandemic period. Nevertheless, an epidermal system that fuses the function and information among all LM-based epidermal devices is needed. In the future, a package of LM-based healthcare systems could be achieved. When patients encounter some general sickness or are willing for a health status check, LM-based healthcare devices could collect their physiological signals by cloud-medicine-assisted wearable devices efficiently and immediately. In these cases, the cooperation of various sensors, electrodes, signal collection and processing, and wireless connections should be extensively considered.To summarize, LM, especially for Ga-based alloys, with high conductivity and excellent stretchability provides a huge potential for next-generation epidermal healthcare devices. For stretchable electronics in the epidermal system, the ‘


Chronic kidney disease (CKD) patients with coronary artery disease (CAD) in the intensive care unit (ICU) have higher in-hospital mortality and poorer prognosis than patients with either single condition. The objective of this study is to develop a novel model that can predict the in-hospital mortality of that kind of patient in the ICU using machine learning methods.Data of CKD patients with CAD were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Boruta algorithm was conducted for the feature selection process. Eight machine learning algorithms, such as logistic regression (LR), random forest (RF), Decision Tree, K-nearest neighbors (KNN), Gradient Boosting Decision Tree Machine (GBDT), Support Vector Machine (SVM), Neural Network (NN), and Extreme Gradient Boosting (XGBoost), were conducted to construct the predictive model for in-hospital mortality and performance was evaluated by average precision (AP) and area under the receiver operating characteristic curve (AUC). Shapley Additive Explanations (SHAP) algorithm was applied to explain the model visually. Moreover, data from the Telehealth Intensive Care Unit Collaborative Research Database (eICU-CRD) were acquired as an external validation set.3590 and 1657 CKD patients with CAD were acquired from MIMIC-IV and eICU-CRD databases, respectively. A total of 78 variables were selected for the machine learning model development process. Comparatively, GBDT had the highest predictive performance according to the results of AUC (0.946) and AP (0.778). The SHAP method reveals the top 20 factors based on the importance ranking. In addition, GBDT had good predictive value and a certain degree of clinical value in the external validation according to the AUC (0.865), AP (0.672), decision curve analysis, and calibration curve.Machine learning algorithms, especially GBDT, can be reliable tools for accurately predicting the in-hospital mortality risk for CKD patients with CAD in the ICU. This contributed to providing optimal resource allocation and reducing in-hospital mortality by tailoring precise management and implementation of early interventions.The online version contains supplementary material available at 10.1186/s40001-023-00995-x. In the past few decades, chronic kidney disease (CKD) has become increasingly prevalent among various countries and regions around the world, increasing the enormous financial burden of many countries . A majorMachine learning (ML) is a cutting-edge technology with the rapid development of artificial intelligence . CompareThe purpose of our study is to (1) construct novel predictive models based on the various machine learning algorithm for in-hospital mortality of patients with CAD and CKD in intensive care units (ICU); (2) select an ML model with the best predictive performance and clinical value; and (3) validate these ML models via external set from the Telehealth Intensive Care Unit Collaborative Research Database (eICU-CRD) database.Data from the MIMIC-IV database were used in this study to establish predictive models for patients with CKD and CAD . MIMIC-IAll patients diagnosed with CAD and CKD were included in this study. Patients who stayed in ICU for less than 6 h, less than 18 years old, without baseline creatinine results, and with missing data > 30% were excluded. Only the first admission was taken into account if a patient had multiple admissions. Baseline creatinine was defined as the creatinine level in the patient's first blood test after hospital admission. Data of demographic information, lab results, hourly vital signs, comorbidities, medications , operative procedures, ICU stay details, and in-hospital mortality were extracted from MIMIC-IV and eICU-CRD database using pgAdmin PostgreSQL tools (version 1.22.1).Variables with > 30% missing values were dropped, and multiple imputations were conducted for other vacant data. Multivariate Imputation by Chained Equations (MICE) was performed and returned an object containing five complete datasets. Then, statistical models such as linear regression or generalized linear model were applied to each complete dataset in turn for interpolation modeling. The pool function consolidates these individual analysis results into a group. The complete dataset is finally returned based on the standard errors and P-values of the model. MIMIC-IV and eICU  databases were imputed separately using the fully conditional specification to avoid data leakage via the “mice” package in R .Z-score between the actual features and shadow features calculated via Random Forest Classifier in each iteration. If the Z-score of an actual feature was higher than the maximum Z-score of shadow features, this feature was considered pivotal and kept; otherwise, it was dropped [Feature selection was a crucial process of reducing the number of features in a massive dataset according to the importance of the study variables. The Boruta algorithm was a wrapper method for feature selection built around the Random Forest Classifier algorithm. During the model construction, Boruta created a copy of the original dataset features as Shadow Features and compared the  dropped .Patients were divided into two groups according to whether they survived to discharge. Categorical variables were summarized as numbers with percentages and compared by Fisher’s exact probability method (or Chi-square tests). The Wilcoxon rank sum test was used to test continuous variables that were expressed as the median with interquartile ranges.Eight machine learning models, including logistic regression (LR), random forest (RF), Decision Tree, K-nearest neighbors (KNN), Gradient Boosting Decision Tree Machine (GBDT), Support Vector Machine (SVM), Neural Network (NN), and Extreme Gradient Boosting (XGBoost), were established to develop the predictive models. 70% of the patients from MIMIC-IV were randomly extracted as the training set, while the remaining 30% was utilized for internal validation. Tenfold cross-validation was performed in each model to prevent overfitting to acquire average accuracy. The performance of each model was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and average precision (AP) from precision/recall (P-R) curves in the validation set. Further, the model with the best performance was picked up to recognize the risk factors most related to in-hospital deaths interpreted by Shapley Additive Explanations (SHAP) method. The SHAP value visually exhibited each feature's importance and contribution to in-hospital mortality. In addition, data from eICU-CRD were used as external validation to assess the prediction model's performance. Decision curve analysis (DCA), AUC, and calibration curves were conducted to evaluate the clinical application and the consistency of the predictive probabilities.P-value lower than 0.05 (two-sided) was regarded as statistically significant.All statistical analyses, machine learning algorithms, and SHAP were implemented via Python (version 3.9.12). The Boruta algorithms were conducted by R . A P < 0.001).A total of 3590 CKD patients with CAD from MIMIC-IV and 1657 CKD patients with CAD from eICU-CRD were included in this study cohort according to the inclusion and exclusion criteria. Figure Z-values, the top twenty variables are the history of cardiac arrest, sequential organ failure assessment (SOFA) score, the maximum values of aspartate aminotransferase (AST) and phosphate, the average values of spo2, white blood cell (WBC), AST, systolic blood pressure (sbp), sodium and platelet, and the minimum values of oxyhemoglobin saturation (spo2), SBP, heart rate, WBC, AST, glucose, phosphate, partial thromboplastin time (PTT), and mean blood pressure (mbp). Although the Z-values for acute coronary syndromes and diabetes were lower than the maximum Z-value of shadow feature, they were included in the analyses based on clinical experience. Therefore, a total of 78 variables were selected for the machine learning model development process.According to the Boruta algorithm analysis, 76 of 124 variables most closely associated with in-hospital mortality were selected  is tightly associated with cardiac death in CKD patients . A natioWhether Coronary Artery Bypass Grafting (CABG) or PCI is the better approach for revascularization of CAD in CKD patients was still controversial. Several observational studies reported CABG was associated with lower mortality than PCI in CKD patients –21. But A growing number of machine learning applications in cardiovascular medicine have been made possible by the development of artificial intelligence , 25. UsiThe GBDT algorithm, also known as the multiple additive regression trees, has more accurate predictive ability and sophisticated algorithms than the LR, decision tree, and random forest algorithms . It has CoronaVirusDisease2019 outbreak. Public databases have helped tide clinical workers over worldwide. But more prospective multicenter clinical studies should also be established for further research.The advantages of this study were that it was the first study focusing on the in-hospital mortality for CKD patients with CAD in ICU based on a public database and constructed an ML model to predict it with external validation. Some limitations must be acknowledged. First, MIMIC-IV was a single-center database; most white patients may lead to racial bias and limit the applicability to other populations. However, external validation was applied using data from a multicenter database, eICU-CRD. Second, the deviation of missing data was inevitable because the data were extracted from the open public database. We performed fully conditional specification (FCS) implemented by the MICE algorithm to multiply and impute the missing data. Third, the selection bias was inevitable because this was a retrospective and observative study. Data were extracted from two different databases as internal and external sets, and further multicenter and large-scale clinical research was still needed. Nevertheless, the constructed ML model still may contribute to clinicians improving the prognosis and treating CKD patients with CAD at high risk in ICU timely. Collecting clinical data on ICU patients have been difficult due to the impact of the In conclusion, machine learning algorithms can be reliable tools for accurately predicting the in-hospital mortality risk for CKD patients with CAD in the ICU. GBDT technology had the best predictive performance, which may provide optimal resource allocation and reduce in-hospital mortality by tailoring precise management and implementing early interventions.Additional file 1: Fig. S1 Subgroup analysis showed via SHAP plot stratified by ACS. A: Impact of each feature on the in-hospital mortality in non-ACS patients; B: Impact of each feature on the in-hospital mortality in ACS patients.Additional file 2: Fig. S2 Subgroup analysis showed via SHAP plot stratified by dialysis. A: Impact of each feature on the in-hospital mortality in non-dialysis patients; B: Impact of each feature on the in-hospital mortality in dialysis patients.Additional file 3: Table S1 Baseline characteristics of CKD patients with CAD in the external validation set (eICU-CRD).


Our aim was to analyze the literature regarding the prevalence of psychological distress and its impact on patients with non-metastatic or metastatic RCC; (2) Methods: A systematic search of five databases was performed. Studies were considered eligible if they included patients with RCC, had a prospective or retrospective design, and assessed anxiety, depression, or psychological distress at any time during treatment or follow-up. Exclusion criteria: no treatment for RCC, or not providing data for RCC patients; (3) Results: A total of 15 studies were included. Reported psychological distress was up to 77% and the prevalence of depressive and anxiety symptoms were up to 77.6% and 68.3% in patients with non-metastatic RCC. There was no association of depression with overall survival (OS) in patients with non-metastatic RCC treated by radical nephrectomy; on the contrary, in patients with metastatic disease, depression had an impact on OS. Limitations are related to the quality of the included studies; (4) Conclusions: Patients with RCC reported a high level of psychological distress like other cancer patients. It seems that for patients with localized disease, psychological distress does not impact OS, while it does in those with metastatic disease. In pracCancer patients with psychological distress (symptoms of depression and anxiety) seem to have higher cancer-specific and overall mortality. Indeed, according to a recent meta-analysis, clinical depression and anxiety significantly increased the risk of cancer incidence , cancer-specific mortality , and all-cause mortality  in cancer patients [Depression and anxiety incidences were reported to be high in patients with urological cancers: 70% in patients with bladder cancer , 17% in To fill this void, we performed a systematic review to analyze the existing literature regarding the incidence of psychological distress, depression and/or anxiety and their impact on oncological outcomes in patients with non-metastatic and metastatic RCC separately.A systematic search of Web of Science, PubMed, Embase, Clinicaltrials.gov, and American Psychological Association (APA) PsycNet was performed on 1 April 2022, using any combination of the terms: anxiety (EXP) OR depression (EXP) OR psychological distress (EXP) AND nephrectomy (EXP) OR renal carcinoma (EXP) OR kidney cancer (EXP). All original articles that fulfilled the inclusion criteria were included. Additional crosschecking of reference lists and hand search to find additional studies was also performed in Google Scholar . www.prisma-statement.org (accessed on 30 August 2022)) [The protocol of this systematic review followed the Cochrane handbook  and the t 2022)) . The preThe PICOS  approach was utilized to define study eligibility. Initial studies were considered eligible if they reported psychological distress (P) before nephrectomy for renal cancer (I) and reported psychological distress after nephrectomy at specific time points during follow-up (C) to determine if there is a change in psychological distress status (O), using validated scales (S). However, only one study met this criteria , so we dThe primary outcome was the prevalence of anxiety, depression and/or psychological distress among patients with non-metastatic and metastatic RCC separately. The secondary outcome was the impact of anxiety, depression and/or psychological distress on outcomes of patients with non-metastatic and metastatic RCC, separately. For each selected study, the following items were recorded independently by two investigators (L.V and M.D.V): first author’s name, year of publication, country, design, number of patients, treatment option, patients’ characteristics, questionnaires used, reported results  and follow-up. Two investigators (L.V and M.D.V) independently manually conducted a literature search and extracted data from the included full-text articles; disagreements were resolved by consensus.Study quality was determined by the Newcastle-Ottawa Scale (NOS)  for cohoThe “risk-of-bias” (RoB) evaluation of each study was assessed according to the Cochrane Handbook for systematic reviews of interventions for including non-randomized studies. RoB was determined by examining the risk of pre-assigned confounders. The main confounding factors were age, gender, marital status, socioeconomic status, and occupation. The presence of confounders was determined by consensus .A total of 6873 abstracts and titles were initially identified in all five databases. After removal of reviews, meeting abstracts, books, and duplicates, 669 remained. Then, 645 articles were excluded after screening titles and abstracts. We assessed 24 full text articles and, finally, 15 studies were included . Ten studies assessed the prevalence of psychological distress, anxiety and/or depression in non-metastatic RCC , two the’low risk of bias’ (in green) and 13 studies had a ’high risk of bias’  [Another meta-analysis reported an even lower probable prevalence during the COVID-19 pandemic for anxiety , depression , and psychological distress  . Due to  < 0.01) .However, when analyzing the data regarding the impact of distress, depression, or anxiety on oncological outcomes in patients with non-metastatic RCC, it seems that these conditions have no influence on mid- and long-term outcomes. This may be related to the good overall prognosis of non-metastatic RCC  and probConversely, in metastatic disease, we found that a high level of distress and depression is associated with OS; other endpoints were not analyzed, such as recurrence, progression, or cancer-specific survival. This correlation was also shown in both bladder and prostate cancers . It is oThe present systematic review analyzed the up-to-date data regarding the prevalence and the impact of psychological distress, anxiety and/or depression, on patients with non-metastatic or metastatic RCC. However, some limitations should be pointed out such as the poor quality of the data, risk of bias, lack of randomized clinical studies and standardization of the reported results that prevailed when performing a meta-analysis.Patients with RCC reported a high level of psychological distress similar to that of patients with other urological malignancies. It seems that for patients with localized disease, these symptoms had no impact on oncological outcomes. Conversely, in metastatic disease, psychological distress is associated with worse outcomes. The impact of psychological distress on therapy adherence and long-term wellbeing warrants further research. Providers, patients, and families need awareness and targeted interventions to identify and help affected patients in a sensitive and effective manner.


Introduction: There is a pressing demand for the development of cancer-specific diagnostic imaging tools, particularly for staging of pancreatic-, gastric- or cholangiocarcinoma, as current diagnostic imaging techniques, including CT, MRI and PET using FDG, are not fully adequate. The novel PET-tracer “FAPI” has the potential to visualize even small tumour deposits employing the tumour-specific expression of fibroblast-activating protein (FAP) in malignant cells. Methods: We performed a systematic review to select studies investigating the use of FAPI PET for staging pancreatic-, gastric- and cholangiocarcinoma (PROSPERO CRD42022329512). Patient-wise and lesion-wise comparisons were performed for primary tumour (T), lymph nodes (N), organ metastases (M) and peritoneal carcinomatosis (PC). Maximum standardized uptake values (SUVmax) and tumour-to-background ratios (TBR) were compared between PET using FAPI versus FDG (if reported). Results: Ten articles met the inclusion criteria. In all studies, FAPI PET showed superiority over FDG-PET/CT/MRI for the detection of T, N, M and PC, both in the patient-wise and in lesion-wise comparisons (when performed). Additionally, higher SUVmax and TBRmax values were reported for use of FAPI compared to FDG. Conclusions: The positive results of this review warrant prospective clinical studies to investigate the accuracy and clinical value of FAPI PET for diagnosing and staging patients with pancreatic-, gastric- and cholangiocarcinoma. The use of sophisticated imaging techniques, such as contrast-enhanced computed tomography (hereafter referred to as CECT), magnetic resonance imaging (MRI) and positron emission tomography (PET) has become the standard of care in the diagnostic work-up and follow-up of cancer patients. For a wide range of indications, PET employing a [18F]-2-Fluoro-Deoxy-Glucose (FDG) tracer enables the detection of increased glycolysis present in cancer cells, even in the absence of—or preceding—structural abnormalities. However, as glucose metabolism is ubiquitous in the human body, especially smaller lesions may suffer from insufficient lesion-to-background signal ratios, limiting the sensitivity of FDG. Additionally, as FDG not only accumulates in cancer cells but likewise in areas of infection and inflammation, specificity is limited.Particularly in preoperative staging of a potentially curable pancreatic-, gastric- or cholangiocarcinoma, accurate imaging plays a crucial role. In contrast to other abdominal tumours, including colon carcinoma and ovarian carcinoma, positive distant lymph nodes, organ metastases or peritoneal/omental implants preclude any surgical resection. In these cases, patients will be offered alternative therapies, including palliative and supportive care. Currently, ubiquitously available imaging techniques, including FDG PET, CECT and MRI, are known to be largely unsatisfactory for this indication. For this reason, surgical exploration by laparoscopy is performed prior to eventual curative surgery in order to detect the possible localisations of tumour spread that are under detected by imaging. The yield of this invasive procedure, however, is low  with moderate sensitivity of 71% ,3. The uRecently, it was discovered that cancer-associated fibroblasts show a high expression of fibroblast activation protein (FAP), while expression levels in normal human tissues are generally very low . This paThis systematic review adheres to the international PRISMA-DTA guidelines for Systematic Reviews and Meta-Analysis of Diagnostic Test . The resA systematic search of current literature on FAPI PET was performed initially in June 2021 and updated in April 2022. A biomedical information specialist was consulted to ensure that all relevant keywords and synonyms were included in the search. Precise search terms can be found in the This systematic review focused on diagnostic studies into pancreatic-, gastric- and cholangiocarcinoma, either as main focus or in combined investigations with other types of tumours. All subtypes of either of these cancer entities were considered eligible for analysis. Reviews and animal studies were excluded. Other exclusion criteria were as follows: the article was not written in English, the study did not focus on the diagnostic tests of interest CT MRI) and the study did not report original numbers to calculate true positives, false positives, true negatives and false negatives for either of the diseases individually.All papers were screened by SV and KP independently for methodological quality using the QUADAS-2 assessment tool . All potIn the subsequent full text analysis of the selected articles, the following study and patient characteristics were retrieved if available: year of publication, study design (prospective or retrospective), the number of participants, and gender and age of the patients. Per article, for each tumour type of interest , the number of detected lesions by FAPI PET and FDG PET and/or (CE)CT and or MRI, were extracted for primary tumour, lymph nodes, organ metastases and peritoneal carcinomatosis . If sufficient detailed information was available, both patient-wise and lesion-wise comparisons were performed. For patient-wise analysis, the number of patients with positive outcomes by FAPI PET and by FDG PET and/or (CE)CT and or MRI were registered. For lesion-wise analysis, the number of detected lesions by each of the imaging techniques were registered for all of the study parameters, T/N/M/PC, individually. Additionally, the used reference standard  was noted when reported. If pathological proof or follow-up imaging was available, sensitivity was calculated accordingly. The methodology was chosen in such manner that a meta-analysis could be performed in case of sufficient data quality.In addition, maximum standardized uptake values (SUVmax) and maximum target to background ratios (TBRmax) were extracted from each article and used for both patient-wise and lesion-wise comparisons between FAPI PET and FDG PET/CT/MRI.n = 7), editorial letters (n = 2), poster presentations (n = 5), technical papers or animal studies (n = 4)). Another nine were excluded because they did not meet the relevance criteria  and three for not reporting numeric data. Finally, ten articles met all inclusion criteria and were further analysed Ga-DOTA-FAPI-46 .Per study, a median total of 27 patients were included (range 13–68), of which only a few (indicated by >) suffered from the cancer types of our specific interest. The median age of patients was 60 years (range 24–87 years). Six studies compared the use of FAPI PET-CT with FDG PET-CT; one study compared FAPI PET-CT with FDG PET-CT, CECT and MRI; two studies compared FAPI PET-CT with CECT ; and one study compared FAPI PET-MRI with FDG PET-CT. The radiopharmaceuticals that were used were [The results of methodological quality screening using QUADAS-2 are shown in In three studies the risk of bias with regards to the reference standard (column 5) was considered high for metastatic lesions (not for primary tumour), because the pathological confirmation or imaging follow-up (>3 months) of some of the detected lesions was missing. In the other QUADAS-2 domains of the studies, no certain or significant risks of bias were found.n = 9), histological proof or follow-up imaging (>3 months) was obtained , compared to FDG PET (column 7), regardless of the additional use of CT or MRI.Shi et al.  reportedn = 1), Rohrich [n = 8/19) and Pang et al. [n = 12/26). In the latter two studies, pancreatic carcinoma could be differentiated from underlying pancreatitis by increasing/stable vs. decreasing uptake over time .Diffuse high uptake in pancreatitis was observed by Chen  (n = 1), Rohrich   versus non-cirrhotic (n = 8) liver parenchyma (SUVmean 1.39 vs. 0.46), which was, however, still significantly lower than the uptake observed in hepatocellular carcinoma and intra-hepatic cholangiocarcinoma (SUVmax 13.6). These findings correlated with the results of Guo et al. [n = 2); similarly, Guo et al. [n = 4) and inflammatory granuloma (n = 1) in liver, as well as positive FAPI uptake in pulmonary infection (n = 1) and thyroid adenoma (n = 1). Chen [Shi et al.  reportedo et al.  . Chen  and Pang1). Chen  et al. f1). Chen . Other s1). Chen , a corpu1). Chen  and a ve1). Chen .n = 2), pancreatic cystadenoma (n = 1), hepatic adenoma (n = 1) [n = 2) [Benign lesions that did not show significant uptake on FAPI PET (resembling or non-significantly differing from FDG uptake) were: esogastritis ( (n = 1) , benign  [n = 2) , haemang [n = 2) . In cont [n = 2)  reportedChen et al.  reportedIn all studies, both the SUVmax as well as the TBRmax were markedly higher for primary tumours, lymph nodes, and organ- and peritoneal/omental metastases when FAPI PET was used compared to FDG PET .This study investigates the diagnostic yield of the novel FAPI PET technique, combined with either CT or MRI, by means of a systematic review and intra-patient and per-lesion head-to-head comparisons with conventional diagnostic techniques, including CT and MRI, either as stand-alone or combined with FDG PET in pancreatic-, gastric- and cholangiocarcinoma. Despite the small number of studies that yet have been conducted, our results point towards a clear benefit of FAPI PET compared to the currently prevailing diagnostic techniques.The results of our literature review show that FAPI PET was able to detect more patients with primary disease and/or nodal-, organ- and peritoneal/omental metastases. Secondly, a larger number of lesions per patient could be identified using FAPI PET, thereby providing a better estimation of disease extension and tumour load. This indicates that FAPI PET is a promising technique for diagnosing and staging pancreatic-, gastric- and cholangiocarcinoma and warrants prospective studies in larger patient groups to enable the further quantification of its clinical value and cost-effectiveness.Other than preoperative staging, FAPI PET may also prove to be of value for staging before and during chemotherapy, in that it could serve as a valuable novel imaging biomarker for the follow-up of treatment response, in addition to use of the currently prevailing Response Evaluation Criteria in Solid Tumours (RECIST). Our head-to-head comparisons show that FAPI PET, compared to FDG PET, consistently provides higher SUVmax and TBRmax values for tumour detection. This is particularly beneficial for the detection of smaller lesions and lesions located in close proximity to abdominal structures with physiological tracer uptake . The highest physiological uptake of FAPI in the abdomen was found in kidneys, pancreas, spleen and colon, with SUV values equalling those of FDG . Physioln = 6/14), hepatic metastases (n = 3) and uterine/rectal metastases (n = 1) with use of MRI (combined with FAPI PET) compared with FDG PET-CT in patients with gastric carcinoma. Sensitivities for comparative CECT used by Rohrich et al. [With respect to the other imaging techniques investigated; Guo et al.  reportedh et al.  and CECTh et al.  were notWith regards to novel therapeutic strategies for pancreatic-, gastric- and cholangiocarcinoma, FAPI also offers theranostic potential, meaning that its ligand can be bound to either diagnostic or therapeutic radioisotopes. Thus, not only can the ligand be labelled with gallium-68 for imaging but also with other radioisotopes emitting therapeutic radiation, such as yttrium-90, lutetium-177, holmium-166 or terbium-161. A great deal of research, however, is still needed to define the optimal isotope for each disease anew as the different histologies of various cancers may sometimes favour one over the other. Here, studies in the preclinical arena are still necessary before even thinking of progressing towards trials in humans.n = 10) were available for review. Of these, some were performed by the same research group and possible overlap of patient data could not be ruled out completely based on the reported information in the manuscripts. Additionally, most studies included different subtypes of tumours. For example, intrahepatic as well as extrahepatic cholangiocarcinoma, gastric tubular adenocarcinoma and diffuse type signet-ring cell carcinoma. Additionally, there was a large variation in disease stage at which patients were included, as well as in treatments given to the patients. This could have influenced reported outcomes, for instance because of varying tumour sizes known to relate to detectability in PET studies. The resulting range, from treatment naive patients to patients that underwent re-staging after therapy, may introduce bias with regards to possible specific sensitivities/specificities for primary staging and restaging.The several limitations of this systematic review need to be addressed. First, given the relative novelty of the FAPI tracer, only a small number of studies  was lacking or incomplete in some studies, particularly for  metastases in patients with a large number of lesions. It was therefore not always assured that all detected lesions by FAPI PET, particularly those not detected by FDG PET, were true-positive lesions. Additionally, although most studies reported separate results for each investigated tumour type, the analyses of metastatic lesions were often performed for multiple tumour types combined. Furthermore, metastatic lesions in different anatomical locations  were not always analysed separately, hampering detailed analysis and resulting in large heterogeneity in SUVmax and TBRmax values.Notwithstanding these limitations, the results of our review and head-to-head comparisons indicate that the introduction of FAPI PET in the diagnostic work-up of patients with pancreatic-, gastric- or cholangiocarcinoma will likely result in better staging and treatment planning, thus fulfilling a high unmet need and adding great clinical value.The results of this systematic review and patient-wise and lesion-wise comparisons clearly show the great potential that FAPI PET-CT/-MRI holds for diagnostic imaging in gastric-, pancreatic- and cholangiocarcinoma, allowing for more accurate staging and possibly better patient-tailored treatment strategies and decision making. Based on these promising results, FAPI PET/CT/MRI will likely supplement or replace FDG PET/CT/MRI and possibly even exploratory laparoscopy in the diagnostic work-up of the cancer types here investigated. However, larger studies with more extensive tissue sampling or imaging follow-up seem desirable for a better assessment of the sensitivity and specificity of this novel radiotracer. Additionally, apart from diagnostic accuracy, the benefits in terms of patient-relevant outcome measures, such as overall and progression-free survival and the eventual theragnostic use of FAPI PET, are still to be assessed.


As a highly aggressive disease, cancer has been becoming the leading death cause around the world. Accurate prediction of the survival expectancy for cancer patients is significant, which can help clinicians make appropriate therapeutic schemes. With the high-throughput sequencing technology becoming more and more cost-effective, integrating multi-type genome-wide data has been a promising method in cancer survival prediction. Based on these genomic data, some data-integration methods for cancer survival prediction have been proposed. However, existing methods fail to simultaneously utilize feature information and structure information of multi-type genome-wide data.We propose a Multi-type Data Joint Learning (MDJL) approach based on multi-type genome-wide data, which comprehensively exploits feature information and structure information. Specifically, MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned multiple correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representation matrix and fused similarity matrix, MDJL constructs graph convolutional network with Cox loss for survival prediction.Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction. Cancer has been becoming the leading death cause all over the world, which seriously affects human health and living quality , 2. In aHistorically, cancer survival prediction works mainly based on histopathological descriptors and low-dimensional clinical data, such as sex, age at diagnosis, cancer grade detail, body fat rate and other clinical features –14. HoweDuring the past several years, many researchers have been devoted to construct data-integration methods based on binary classification models for cancer survival prediction. In this technology, cancer patients are usually classified to the short or long survival group according to a predefined threshold . For example, Zhang et al.  presente(i) simultaneously utilizing structure information and feature information, specifically for small scale dataset; (ii) fully utilizing multi-type data for learning effective discriminant features. Here, structure information points to the information of data distribution within data types. Feature information refers to the information contained in the data (such as genes) within a sample. Discriminant features refer to the features learned from original data (such as gene sequences) by utilizing feature learning algorithms, which is useful to separate the samples with different survival time [Although existing works have promoted the development of data-integration methods in cancer survival prediction, there are two limitations to develop this technology: val time . ExistinInspired by the above analysis, we intend to design a Multi-type Data Joint Learning (MDJL) approach to obtain a reliable similarity matrix for exploiting structure information and an effective discriminant feature representation for exploiting feature information. In our proposed MDJL, (a) structure information and feature information can be simultaneously utilized; (b) the discriminant feature representations are exploited by learning correlation representations between any two data types, which can ensure the diversity and provide complementary information; (c) the constructed similarity matrices can explore useful structure information even from a small-scale samples.Different from existing survival prediction methods, we present a Multi-type genome-wide Data Joint Learning (MDJL) approach for cancer survival prediction, which achieves both a fused similarity matrix and an integrated discriminant feature representation for simultaneously utilizing structure information and feature information.MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representations and similarity matrices, MDJL constructs graph convolutional network with Cox loss for survival prediction.We conduct a number of experiments on four public cancer datasets. Experimental results show that our approach can achieve higher prediction performance than competing methods. Further investigation not only demonstrate the effectiveness of each component for MDJL, i.e., correlation representations extraction component and similarity matrices construction component, but also indicate the robustness.The main contributions of our approach lie in three aspects: The rest of this paper is organized as follows: Sect. In the past few decades, a variety of binary classification based multimodal learning methods for survival prediction have been proposed. In general terms, a modality refers to a kind of data type. These methods mainly focus on learning fused representation from multiple data sources, such as clinical data, histopathological images markers and genomic data –31. WithDifferent from binary classification methods, the survival risk regression methods aim to calculate a risk score for each patient, typically with the Cox-PH model and its extensions –43. For Recently, with the excellent data representation ability and high learning ability, a variety of deep neural networks extension of the Cox-PH model has been proposed –50. For Similarity matrix construction has been widely used in multi-view clustering tasks. Usually, existing methods tend to construct similarity matrix for each data types, based on which they learn a shared similarity matrix of all data types. For example, Zhan et al.  learned In this paper, we propose a Multi-type Data Joint Learning (MDJL) approach for cancer survival prediction based on multi-type genome-wide data. Specifically, instead of exploiting common feature information shared by all data types, we exploit correlation/common feature information between any two data types for exploring diverse and complementary feature information across multiple data types. Secondly, we fully utilize the global and local structure to construct similarity matrices based on the learned multiple correlation representations. Here, global structure refers to the similar structure information across different data types, local structure refers to the neighborhood information within data types. The main architecture of our MDJL approach is illustrated in Fig. N samples and V different data types. Let v-th data type, and i-th sample of data type v, V neural networks l-th layer l-th layer Suppose there are i-th sample, the interactive map To further explore the correlation representations between any two data types, we borrow correlation computation proposed in . FollowiBased on the interactive map set, we further construct a set of neural networks Based on the above subsections, we have learned multiple correlation representations from multiple data types. The finally fused correlation feature representation from all pairwise data types can be written as,M different correlation feature representations m-th correlation representation m-th correlation representation. To integrate these similarity matrices constructed from multiple correlation representations, we introduce a normalized weight matrix As mentioned above, MDJL aims to learn a fused similarity matrix based on multi-type data. The reliability of the similarity matrices constructed from raw data may be polluted severely by noise and outliers. To enhance the ability to resist noise and outliers, we construct similarity matrices based on the learned multiple correlation representations. By correlation information learning, we collect In order to measure local similarity, we design a sparse kernel based on K nearest neighbors (KNN), that is:To obtain fused similarity matrix, we iteratively update m-th correlation representation, we iteratively update T iterations, the learned For P. Then the P were used as the input of graph convolutional network for model training and prediction. In this paper, we construct the graph convolutional network G with added self-connections. l-th layer, l-th layer  is the censorship flag. If sample i is uncensored sample, i is censored sample, i, where patient i should be uncensored samples. j-th sample is longer than that of i-th sample, where patient j can comes from either uncensored samples or censored samples.To describe the effectiveness of quantitative variables on survival time, we introduce Cox loss as loss function , that isV data types, the sample set For each of the mentclass2pt{minimAlgorithm 1 describes the process of cancer survival prediction by using MDJL.http://compbio.cs.toronto.edu/SNF/, which are provided and preprocessed by work [Four cancer datasets by work . It downMKL + Cox loss (MKL-Cox). MKL is a multiple kernel learning based binary classification method for cancer survival prediction, which fuses multi-type data using joint strategy . For a fMDNNMD + Cox loss (MDNNMD-Cox). MDNNMD is a multimodal deep neural network based binary classification method for cancer survival prediction, which fuses multi-type data using joint strategy . For a fDLMR. DLMR is a multimodal deep neural network extension of the Cox model for cancer survival prediction, which fuses multi-type data using alignment strategy .CrossAE. CrossAE is a cross-modality autoencoder based survival prediction method for utilizing the consensus representations across multi-type data .VAECox. VAECox is a deep transfer learning architecture for cancer survival prediction based on alignment strategy .DeepSurv. DeepSurv is a deep learning generalization of the Cox proportional hazards model, which predicts survival risks based on single-type data . For comThe implementations of MDNNMD-Cox, DLMR, CrossAE, VAECox and DeepSurv are downloaded from the websites provided by their authors. With there are no public codes for MKL-Cox, we implement MKL-Cox by ourselves.To evaluate the performance of our MDJL approach, we compare it with several state-of-the-art cancer survival prediction methods:K=20, and T=30 in similarity matrix fusion algorithm. In this paper, the concordance index (C-index) is adopted to evaluate the performance of the competing survival prediction models, which mainly measures the proportion of all sample pairs for which the predictions and actual results are consistent. In order to guarantee fairness and robustness of research methods, for each dataset, we conduct 20 trials for each compared method, and the average performance of 20 trials is reported. For each trial, we would re-split the training and testing sets with 70% data for training and 30% data for testing, and re-fit the models. The corresponding Python code for carrying out our method is available at https://github.com/githyr/MDJL_Survival.All these methods are evaluated on GBM, KRCCC, LSCC and BIC datasets. For each cancer dataset, we randomly select 70% data for training and utilize the rest of 30% for testing. The details of network architecture for MDJL are as follows: For feature learning, we design the networks The predictive results of all competing methods are reported in Fig. We further investigate our MDJL approach with survival analysis which can be regarded as a statistical method considering both results and survival time. The patient samples for each cancer type would be divided into high-risk and low-risk groups based on their predicted hazard ratios. For example, a patient sample would be assigned to high-risk group if his hazard ratio is higher than the median hazard ratios of all patient samples, otherwise, he would be included in low-risk group. We illustrate the Kaplan-Meier (KM) curves in Fig. In this section, we verify the effectiveness of correlation representation extraction. In this paper, we integrate multiple data types for exploiting discriminant features by exploiting correlation information between any two data types, instead of exploiting common information shared by all data types or directly concatenating original multiple data types. In this paper, we call the version of exploiting common information shared by all data types for learning discriminant feature representations as CIAD, and the version of directly concatenating original multiple data types for learning discriminant feature representations as COMD. For CIAD, we exploit shared feature matrix by constructing feature learning networks for each data type and imposing Euclidean distance constraint between the learned feature representations of any two data types, and construct similarity matrices based on original multiple data types. For COMD, we concatenate original multiple data types into a unified feature matrix, and construct similarity matrices based on original multiple data types.We perform MDJL, CIAD and COMD on each cancer dataset respectively for 20 trials and record the C-index score for each performance. For each trial, we would re-split the training and testing sets with 70% data for training and 30% data for testing, and re-fit the models. Figure In this section, we verify the effectiveness of learning structure information based on correlation representations. We respectively perform the model with learning structure information based on correlation representations, the model with learning structure information based on original data, and the model without learning structure information. We call the version that utilizes original multi-type data to construct similarity matrices as MDJL-OS, and call the version of MDJL without learning structure information as MDJL-SI. For MDJL-OS, we utilize original multi-type data to construct similarity matrices and exploit discriminant feature representations by learning correlation information between any two data types. For MDJL-SI, we exploit discriminant feature representations by learning correlation information between any two data types and replace the graph convolutional network with a three-layer fully connected network.We perform MDJL, MDJL-OS and MDJL-SI on each cancer dataset respectively for 20 trials and record the C-index score for each performance. For each trial, we would re-split the training and testing sets with 70% data for training and 30% data for testing, and re-fit the models. Figure To further investigate the effective of the fused similarity matrices respectively learned from multiple correlation representations, we exhibit the fused similarity matrices of the training sets on four cancer datasets in Fig. K and T with fixing any one hyper-parameter and changing the value of another hyper-parameter. When K is evaluated, we set T as 50. When T is evaluated, we set K as 20. We repeat each execution 20 times and record the average C-index. For each trial, we would re-split the training and testing sets with 70% data for training and 30% data for testing, and re-fit the models. Figure K and T on GBM and KRCCC. From the figure, we can observe that the C-index of MDJL on GBM and KRCCC datasets have a small fluctuation range (< 0.2). In general, the proposed approach is insensitive to hyper-parameters K ranging from 5 to 50 and T ranging from 10 to 100.In this section, we investigate the sensitivity for hyper-parameters In this section, we use the model training time iterating over all the datasets 200 times to measure the computing time of MDJL and other baselines. Computing time of all compared methods is collected from a computer with an Intel i7 quadcore 3.6GHz CPU, a NVIDIA GTX1080Ti GPU, and 16GB memory. As seen from Table In this paper, we propose a novel multi-type data joint learning approach, and apply it to the cancer survival prediction task. MDJL integrates correlation representation learning, similarity learning and graph convolutional network construction into a unified framework. Correlation feature representations between any two data types are effectively and fully exploited to learn discriminant feature representations. Global and local structure information among samples is fully exploited to learn the relationships among samples.Extensive experiments on four public cancer datasets demonstrate that our approach can achieve better performance than other competing cancer survival prediction methods. In addition, experiments also demonstrate the effectiveness of the designed modules of our approach.


Diversity in our diet mirrors modern society. Affluent lifestyles and extended longevity have caused the prevalence of diabetes and sarcopenia, which has led to the increased demand of low-carb, high-protein foods. Expansion of the global population and Westernization of Asian diets have surged the number of meat eaters, which has eventually disrupted the supply–demand balance of meat. In contrast, some people do not eat meat for religious reasons or due to veganism. With these multiple circumstances, our society has begun to resort to obtaining protein from plant sources rather than animal origins. This “protein shift” urges food researchers to develop high-quality foods based on plant proteins. Meanwhile, patients with food allergies, especially gluten-related ones, are reported to be increasing. Additionally, growing popularity of the gluten-free diet demands development of foods without using ingredients of wheat origin. Besides, consumers prefer “clean-label” products in which products are expected to contain fewer artificial compounds. These diversified demands on foods have spurred the development of “new” foods in view of food-processing technologies as well as selection of the primary ingredients. In this short review, examples of foodstuffs that have achieved tremendous recent progress are introduced: effective use of plant protein realized low-carb, high protein, gluten-free bread/pasta. Basic manufacturing principles of plant-based vegan cheese have also been established. We will also discuss on the strategy of effective development of new foods in view of the better communication with consumers as well as efficient use of plant proteins. What is expected on food research? It is gratifying that our life expectancy has increased ,2. On thIn the development of new foods, food allergy is one of the most critical issues to tackle . DevelopFood researchers have developed new foods that meet the broad variety of consumers’ expectations. To survey consumers’ preferences effectively, they have enhanced communication skills with customers. In parallel, they have upgraded the processing technologies to test the production of such foods to reflect the survey results appropriately. This review introduces successful examples of such foods: gluten-free bread/pasta and vegan cheese. The trial-and-error as well as strategic approaches exercised thus far provide us with clues for developing future foods.Archaeobotanical evidence shows that the origins of bread date back to 14,400 years ago in northeastern Jordan ,14. Sinc3/g; guar gam, 2.0–2.1 cm3/g). Transglutaminase catalyzes the acyl-transfer reaction between the ε-amino group on protein-bound lysine residues and γ-carboxyamide group of protein-bound glutamine residues [Therefore, development of high-quality gluten-free foods or a vegan menu not particular to the celiac/wheat-allergy patients or vegans but for all consumers will raise the prevalence and availability. The main ingredient of gluten-free bread is non-glutinous cereals such as rice. Generally, a viscosity improver, exemplified by hydroxypropylmethyl cellulose (HPMC) or guar gam, is used as a substitute for gluten . Rice baresidues . Thus, iresidues .3/g, higher than that (1.36 cm3/g) of the control bread [On the other hand, since the first report by Renzetti and Arendt , proteasol bread . A hypot3/g. The swelling mechanism was based on the Pickering foam  compared to the addition of 5 °C water . The authors claim that it is a cost-effective and simple method of producing bread from gluten-free rice flour by applying the thickening effect of gelatinization without the use of specific materials, such as thickening agents or rice flour with controlled starch damage. Ohmic heating: Optimization of the baking process may contribute to improved product quality. Ohmic heating of food products, achieved by passage of an alternating current through food, has emerged as a potential alternative to conventional heating. Key characteristics of ohmic heating are homogeneity of heating, shorter heating time, low energy consumption, and improved product quality and food safety [3/g; relative elasticity, 45.05–56.83%; porosity, 35.17–40.92%) compared with conventional oven-baked GF bread . Moreover, ohmic baking only requires a few minutes to obtain a fully expanded GF bread. Due to its volumetric and uniform heating principle, crumb development during baking and consequently bread volume is improved, which enhances the overall GF bread quality [Partial Vacuum Baking: Baking GF bread under partial vacuum is worth trying. Because water’s boiling point decreases under reduced pressure, it is expected that its distribution within the batter and its interactions with the other constituents, mainly starch, would differ from those in bread baked under atmospheric pressure [3/g; hardness: 17.82 N) compared to the control bread baked at atmospheric pressure . However, the DSC, SEM, and XRD results showed that a more crystalline structure and different starch crystal types formed after partial-vacuum baking. Moreover, partial-vacuum baking significantly affected the total water loss and the texture parameters during storage for three days. Partial-vacuum-baked samples were softer and had a tendency to become stale more slowly than the control. The findings indicate that the partial-vacuum-baking method increases the shelf life of gluten-free products by modifying the microstructure of the bread.Below, the ongoing and quite recent studies on the cereal flour-based gluten-free breads are introduced. nization . Additiod safety . A possid safety . Passaged safety  compared quality . Partialpressure . Şimşek pressure  evaluateThus far, several efforts have been made to develop high-protein, low-carbohydrate bread whether wheat-based or gluten-free. These breads are mostly made by adding plant/animal protein, such as chickpea flour , pea pro3/g) of the bread made from the dough. The maximum specific volume is over 6 cm3/g, comparable to that of the wheat bread. However, the error bars show that controlling the specific volume, that is, stabilizing the swelling ratio of the bread, remains an issue.Recently, development of a high-protein/low-carbohydrate bread was reported . A doughNext, we ask why the soy protein/egg white dough swells upon heating. The mechanism of “aburaage” making is the clue. Aburaage, a fried tofu, is a traditional Japanese cuisine that attracts attention as a healthy soy-based product . Upon frProgress in the development of gluten-free pasta is briefly mentioned here. Recent reviews by other authors cover history, classification, materials, and processing of Asian noodles  as well Generally, dough for noodles is made using water and cereal flours, such as wheat and rice, which are mixed and shaped into long and thin structure to make fresh pasta . In the Recently, a protein-rich pasta made exclusively of yellow pea and water was reported . In termExtrusion cooking expanded the consumption of pulses . MoreoveConventional milk cheese, generally perceived as natural cheese, was born from an accidental curdling of milk. Casein is the main protein in milk. It is hydrophobic and exists as casein micelles. Cheese curdling is decided mainly by this hydrophobic force of casein micelles forming a network structure . In convBecause of the constant pursuit and innovation of cheese making, the original milk cheese was derived from the traditional sense of fermented natural cheese to multiple types of cheese products, such as processed cheese, cream cheese, and cheese analogues, which has led to a diverse and complex structure in cheese. The most common and well-developed cheese product is processed cheese. Processed cheese mainly consists of natural cheese, emulsifying salts, water, and limited amounts of additional ingredients, which are developed based on emulsification. It was clarified that emulsifying salts, water, and additives, such as pre-cooked cheese or starches, had obvious impact on the textural properties of processed cheese. Factually, the changes in textural properties of cheese are substantially affected by casein network structure and fat globules. It was demonstrated that a sufficiently emulsifying with high stirring speed and long stirring time could reduce the sizes of fat globules and cause the casein network structure to become fine-stranded ,73,74,75Recently, plant cheese is coming to the forefront of consumers’ minds . There hThere are primarily two types of approaches in plant-cheese manufacturing . FirstlyIn developing new food products, communication with consumers is critical to meet their demands. To obtain consumer-based perceptual product profiles, the Check-All-That-Apply (CATA) questionnaire has become a popular method for its convenience and effectiveness . ExplainMoreover, friendly and accessible tools with a sense of fun have come into popular use. “Emoticons” are pictorial/textual depictions of facial expressions recently attracting attentions in marketing communications . A combiFurthermore, effective use of familiar tools such as Twitter helps researchers understand consumers’ attitudes. Over 120,000 tweets relating to veganism were extracted from Twitter, which were then analyzed using a text analytics tool to ascertain the predominant themes of conversation taking place around vegan food . Value pEffective use of plant protein in the development of high-protein, low-carbohydrate foods not only complements over-demanded animal protein but also contributes to sustainability . Indeed,Other plant proteins are attracting attention as well. Due to its hard-to-cook characteristics, mung bean had remained underutilized. Recently, however, by optimizing the extrusion parameters, texturized mung bean protein with desirable physical properties has been successfully produced as a candidate for meat extender . MoreoveOn the other hand, some reports raise alarm on a rapid dietary shift from animal to plant protein ,116. ThuTo tackle the global-scale challenges such as protein shift, a food-processing sector supported by the government is indispensable. For example, in the Netherlands, the region of Wageningen has developed a food innovation cluster that involves a large number of food firms, global agri-food incumbents, and leading knowledge and educational institutions, including Wageningen University and Research Center . The FooRapid progress in food-processing technology has realized new plant-based foods almost identical to the original, animal-based ones: plant meat with realistic fiber , plant pRapid growth of human population, global warming, and animal welfare have inspired a protein shift from animal to plant. Rich and aging societies now encounter lifestyle-related diseases, such as diabetes and sarcopenia, which urge food researchers to develop high-protein, low-carbohydrate foods. Celiac/wheat-allergy patients are compelled to follow a gluten-free diet. Thus, food researchers and suppliers have been making efforts to meet multiple consumer needs. Evolution of the food-processing technology has realized authentic-looking gluten-free bread/pasta, plant cheese, soy meat, and other plant-based products. In parallel, researchers have enhanced communication skills with consumers by taking advantage of friendly tools, such as emoticons and Twitter. Effective utilization of a variety of plant proteins will realize development of new foods highly-accepted by consumers with their high nutritional value. Then, what comes next? In the near future, researchers are developing innovative foods by not mimicking but surpassing the original food products unintentionally.