Multi-parameter Detection Research Articles

Three-dimensional multi-parametric surface detection technology based on atomic force microscopy

Three-dimensional multi-parametric surface detection technology based on atomic force microscopy

Realizing Multi-Parameter Measurement Using PT-Symmetric LC Sensors.

With the rapid development in sensor network technology, the complexity and diversity of application scenarios have put forward more and more new requirements for inductor-capacitor (LC) sensors, for instance, multi-parameter simultaneous monitoring. Here, the parity-time (PT) symmetry concept in quantum mechanics is applied to LC passive wireless sensing. Two or even three parameters can be monitored simultaneously by observing the frequency response of the reflection coefficient at the end of the readout circuit. In particular, for three-parameter detection, a novel detection method is studied to extract the three resonant frequencies of the system through the phase-frequency characteristics of the reflection coefficient, which has never appeared in the previous literature on PT symmetry. The changes in three resonant frequencies are in response to changes in the three parameters in the environment. We show theoretically and demonstrate experimentally that the PT-symmetric LC sensor can realize multi-parameter measurement using a series LCR circuit as the sensor and a symmetric adjustable LCR circuit as the readout circuit. Our work paves the way for applying PT symmetry in multi-parameter detection.

Practical design and implementation of IoT-based occupancy monitoring systems for office buildings: A case study

This study introduces a scalable, cloud-based approach to occupancy monitoring designed to optimize HVAC operations in office buildings. It addresses the challenges of developing and implementing a multi-parameter IoT-based occupancy monitoring system by integrating various off-the-shelf sensors—CO2, infrared (IR), motion (PIR), and door status detection—into a cohesive system. Leveraging wireless LoRaWAN and novel cloud technologies, the system ensures easy installation, efficient maintenance, and robust data management. CO2-based occupancy detection models were trained using data from a reference office and validated in another office environment. Among the various models evaluated, the four best-performing ones—Decision Trees, Random Forest, LightGBM, and K-Nearest Neighbors—were selected for integration into a multi-parameter detection system. To further enhance system performance and identify optimal sensor combinations and configurations for cost-effective and accurate occupancy detection, a data fusion methodology was employed. This methodology, validated with ground-truth data from a test bed, tested the monitoring system in different office settings, ranging from single to quadruple-occupant rooms. Integration of additional parameters into the developed data fusion approach significantly improved system performance, achieving a True Positive Rate (TPR) of 95% compared to 81% with a simple baseline data fusion method. This approach also reduced false detections during unoccupied periods, as tested in multiple rooms within the studied building, thereby enhancing the system's reliability for integration into occupancy-aware HVAC control strategies.

Full-size experimental investigations on planetary gear journal bearings in high-power wind turbines

Abstract To satisfy the large-scale and high-power demands of wind turbines, planetary gear journal bearings (PGJBs) have been applied in large wind turbine gearboxes (WTGs), as an alternative to traditional rolling bearings, due to their higher reliability and smaller size. To simulate the actual lubrication behaviors of PGJBs and investigate their hydrodynamic performance, a full-size test rig for PGJBs was built in this paper. A multi-parameter detection system coupled with the ultrasonic testing method was developed. Four ultrasonic piezoelectric elements, eight thermistors, two pressure transducers, and one torque sensor were used to obtain the film thickness, oil temperature, oil pressure, and friction torque data of the test PGJB. The rated condition experiment was conducted to investigate the variation of measured lubrication performance with the operating time. Three-dimensional predictions of oil film pressure, temperature, and thickness were presented to analyze the steady-state lubrication characteristic at the rated condition. Moreover, a series of steady-state experiments were also carried out to simulate the normal operations of the test PGJB at different conditions. And the measured results were verified by the numerical predictions. The influence of rotational speed, input load, oil supply temperature, and oil supply flow on the hydrodynamic performance of the test PGJB were explored.

Research on integrated LiDAR and multi-parameter detection of atmospheric transmittance, turbulence, and wind

An integrated LiDAR system has been reported, which can be used for simultaneous detection of atmospheric transmittance, turbulence, and wind along the same path. Through the integrated design of optics and mechanics, the size and weight of the system were effectively reduced. The comprehensive detection distance of atmospheric transmittance, atmospheric coherence length, and radial wind had also been achieved at least 4 kilometers. Comparative experiments have demonstrated that the detection results of the integrated LiDAR system and the near-surface meteorological observation system have standard deviations of less than 0.03 km−1 for extinction coefficient, 0.2 m/s for wind velocity, and 7.15 × 10−14 m−2/3 for C 2 n (atmospheric refractive index structure parameter), thus verifying the accuracy of the system detection. The reliability of the integrated LiDAR system was validated through six consecutive nights of continuous detection experiments, measuring three parameters simultaneously. Through analysis, the influence laws among atmospheric transmittance, coherence length, and wind were preliminarily explored. Significant variations in wind velocity can induce substantial fluctuations in atmospheric coherence length, and it is positively correlated with atmospheric transmittance. The integrated LiDAR system can provide a variety of reliable real-time detection data for further research on the laser transmission process in the atmosphere.

Dual-modal fiber-optic sensor for simultaneous pH and temperature monitoring in tumor microenvironment

The tumor microenvironment (TME) is a complex system. Temperature, pH, oxygen content, and other biomarkers comprehensively reflect the growth state of the tumor, necessitating a multi-parameter detection strategy to garner the precise status of tumor for treatment guidance. Fluorescence imaging technology is a promising tool for realizing this goal due to its advantages of low cost, real-time responses, and high sensitivity. However, several limitations, including the shallow penetration depth of fluorescence signals in biological tissues and the potential crosstalk between multiple fluorescence signals, hinder the practical application of current fluorescence imaging technology. In this paper, a dual-mode optical fiber sensor consisting of a fiber fluorescence pH sensor and a fiber Bragg grating (FBG) temperature sensor is presented. The compact sensor uses different principles for pH and temperature monitoring, thus effectively eliminating potential crosstalk between different signals. In addition, its small size allows it to be inserted into deep tissues for detection. The sensor responds quickly to changes in pH.Moreover, the temperature sensitivity of FBG packaged with PDMS is 34 % higher than the uncoated FBG. In vivo experiments confirmed that the sensor can accurately distinguish normal tissues and tumor tissues. The proposed sensor provides a novel way to realize multi-parameter monitoring of tumor microenvironment and improve the specificity of tumor detection.

Multi-parameter information detection of aircraft taxiing on an airport runway based on an ultra-weak FBG sensing array.

Tracking the moving state and analyzing the distribution feature of an aircraft taxiing on the pavement are crucial for runway safety management. One challenge is to provide a reliable methodology that would enable such needs to be addressed in long-distance range runway with high sensitivity and spatial resolution. This paper proposed a novel monitoring approach for acquiring multi-parameter information of aircraft taxiing on airport runway based on distributed vibration detected by ultra-weak fiber Bragg grating (FBG) sensing array. For an actual engineering equipped with the smart runway system, the ultra-weak FBG sensing technology was applied to collect the distributed vibration responses of taxiing aircraft in takeoff and landing stages. The monitoring data of the vibration sensing optical cables beneath the entire pavement were directly utilized to evaluate the identification feasibility and effectiveness of taxiing speed and position, landing distribution, and taxiing acceleration and distance based on samples of five representative aircraft types. The results indicated that the speed, position, aiming point offset, acceleration changes and probability distribution of the taxiing distance can be revealed based on actual measurements concerning the distribution of vibration intensity with respect to space and time. Moreover, the analysis demonstrated that the experimental results based on ultra-weak FBG sensing array was able to account for the characteristic of different aircraft types participating in the study and the current operating conditions of the airport.

Early multi-parameter detection study of lithium-ion batteries based on the ratio of blue to infrared light and gas concentration

As the use of lithium-ion batteries in energy storage and transportation grows, the number of fires and explosions caused by battery thermal runaway increases, emphasizing the vital need for enhanced early detection technology. Existing research does not clarify the effect of airflow environment and detection location on battery smoke flow and detection effectiveness. The purpose of this study is to illuminate the environmental effects on battery smoke diffusion, allowing for the selection of more appropriate detection parameters while also improving detection sensitivity and robustness. Here, the investigation focuses on the smoke characteristics of 18650 LiFePO4 (LFP) batteries, using the ratio of blue to infrared light and concentrations of CO and H2. Additionally, a detrending algorithm was developed to interpret smoke signals, and the smoke characteristics of batteries in different states of diffusion after thermal runaway occurred at different states of charge (SOC) were further investigated. It is shown that the smoke signal values processed by the detrending algorithm are more suitable for smoke detection in thermal runaway batteries. Using smoke and fugitive gas growth rate parameters, the results show that airflow interference is important in promoting smoke diffusion. Notably, the ambient state and the SOC of the battery have a greater influence on the maximum concentration of CO compared to H2. The linear equations and the addition of the environmental influence parameter DR imply that H2 is a better choice as the primary gas parameter for identifying battery runaway. The airflow disruption reduced the smoke response time by around 40 % while having minimal influence on gas diffusion. This study establishes a theoretical foundation for optimizing battery operating environments and gives practical guidelines for the use of multi-parameter monitoring and early detection of lithium-ion batteries. Furthermore, this study improves the safe management and protection of lithium batteries in their application.

Multi-mode fiber Bragg grating for simultaneous detection of strain, torsion and temperature

In this study, a fiber Bragg grating sensor utilizing multi-mode optical fiber (MM-FBG) is proposed. This sensor can simultaneously detect both temperature and torsion, or strain and torsion. Unlike single-mode fiber, the multiple modes of multi-mode fiber can generate several reflection peaks within the FBG area, increasing data capacity and enabling multi-parameter detection. By monitoring the center wavelength and reflection intensity of the MM-FBG reflection peaks, the sensor can detect temperature, torsion, and strain simultaneously. This approach simplifies parameter characterization compared to traditional methods, reducing signal interference and enhancing the clarity of experimental results. Experimental findings demonstrate that the MM-FBG sensor structure exhibits maximum sensitivities of 0.571 dBm/°/cm for torsion, 12 pm/°C for temperature, and 0.7411 pm/με for strain. Therefore, the fiber sensor proposed in this study shows great potential for monitoring bridge and tunnel structures and for civil engineering applications.

Multiparameter Mechanical Phenotyping for Accurate Cell Identification Using High-Throughput Microfluidic Deformability Cytometry.

Mechanical phenotyping has been widely employed for single-cell analysis over recent years. However, most previous works on characterizing the cellular mechanical properties measured only a single parameter from one image. In this paper, the quasi-real-time multiparameter analysis of cell mechanical properties was realized using high-throughput adjustable deformability cytometry. We first extracted 12 deformability parameters from the cell contours. Then, the machine learning for cell identification was performed to preliminarily verify the rationality of multiparameter mechanical phenotyping. The experiments on characterizing cells after cytoskeletal modification verified that multiple parameters extracted from the cell contours contributed to an identification accuracy of over 80%. Through continuous frame analysis of the cell deformation process, we found that temporal variation and an average level of parameters were correlated with cell type. To achieve quasi-real-time and high-precision multiplex-type cell detection, we constructed a back propagation (BP) neural network model to complete the fast identification of four cell lines. The multiparameter detection method based on time series achieved cell detection with an accuracy of over 90%. To solve the challenges of cell rarity and data lacking for clinical samples, based on the developed BP neural network model, the transfer learning method was used for the identification of three different clinical samples, and finally, a high identification accuracy of approximately 95% was achieved.

Electrochemical Sensors for Heavy Metal Ion Detection in Aqueous Medium: A Systematic Review.

Heavy metal ions (HMIs) are very harmful to the ecosystem when they are present in excess of the recommended limits. They are carcinogenic in nature and can cause serious health issues. So, it is important to detect the metal ions quickly and accurately. The metal ions arsenic (As3+), cadmium (Cd2+), chromium (Cr3+), lead (Pb2+), and mercury (Hg2+) are considered to be very toxic among other metal ions. Standard analytical methods like atomic absorption spectroscopy, atomic fluorescence spectroscopy, and X-ray fluorescence spectroscopy are used to detect HMIs. But these methods necessitate highly technical equipment and lengthy procedures with skilled personnel. So, electrochemical sensing methods are considered to be more advantageous because of their quick analysis with precision and simplicity to operate. They can detect a wide range of heavy metals providing real-time monitoring and are cost-effective and enable multiparametric detection. Various sensing applications necessitate severe regulation regarding the modification of electrode surfaces. Numerous nanomaterials such as graphene, carbon nanotubes, and metal nanoparticles have been extensively explored as interface materials in electrode modifiers. These nanoparticles offer excellent electrical conductivity, distinctive catalytic properties, and high surface area resulting in enhanced electrochemical performance. This review examines different HMI detection methods in an aqueous medium by an electrochemical sensing approach and studies the recent developments in interface materials for altering the electrodes.

Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels

Multiplexed, real-time fluorescence detection at the single-molecule level can reveal the stoichiometry, dynamics and interactions of multiple molecular species in mixtures and other complex samples. However, fluorescence-based sensing is typically limited to the detection of just 3–4 colours at a time due to low signal-to-noise ratio, high spectral overlap and the need to maintain the chemical compatibility of dyes. Here we engineered a palette of several dozen composite fluorescent labels, called FRETfluors, for multiplexed spectroscopic measurements at the single-molecule level. FRETfluors are compact nanostructures constructed from three chemical components (DNA, Cy3 and Cy5) with tunable spectroscopic properties due to variations in geometry, fluorophore attachment chemistry and DNA sequence. We demonstrate FRETfluor labelling and detection for low-concentration (<100 fM) mixtures of mRNA, dsDNA and proteins using an anti-Brownian electrokinetic trap. In addition to identifying the unique spectroscopic signature of each FRETfluor, this trap differentiates FRETfluors attached to a target from unbound FRETfluors, enabling wash-free sensing. Although usually considered an undesirable complication of fluorescence, here the inherent sensitivity of fluorophores to the local physicochemical environment provides a new design axis complementary to changing the FRET efficiency. As a result, the number of distinguishable FRETfluor labels can be combinatorically increased while chemical compatibility is maintained, expanding prospects for spectroscopic multiplexing at the single-molecule level using a minimal set of chemical building blocks.

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis.

Tumor-derived extracellular vesicles (EVs) carry tumor-specific proteins and RNAs, thus becoming prevalent targets for early cancer diagnosis. However, low expression of EV cargos and insufficient diagnostic power of individual biomarkers hindered EVs application in clinical practice. Herein, we propose a multiplex Codetection platform of proteins and RNAs (Co-PAR) for EVs. Co-PAR adopted a pair of antibody-DNA probes to recognize the same target protein, which in turn formed a double-stranded DNA. Thus, the target protein could be quantified by detecting the double-stranded DNA via qPCR. Meanwhile, qRT-PCR simultaneously quantified the target RNAs. Thus, with a regular qPCR instrument, Co-PAR enabled the codetection of multiplex proteins and RNAs, with the sensitivity of 102 EVs/μL (targeting CD63) and 1 EV/μL (targeting snRNA U6). We analyzed the coexpressions of three protein markers (CD63, GPC-1, HER2) and three RNA markers (snRNA U6, GPC-1 mRNA, miR-10b) on EVs from three pancreatic cell lines and 30 human plasma samples using Co-PAR. The diagnostic accuracy of the 6-biomarker combination reached 92.9%, which was at least 6.2% higher than that of 3-biomarker combinations and at least 13.5% higher than that of 6 single biomarkers. Co-PAR, as a multiparameter detection platform for EVs, has great potential in early disease diagnosis.

Spectrally separated dual-label upconversion luminescence lateral flow assay for cancer-specific STn-glycosylation in CA125 and CA15-3

Multiplexed lateral flow assays (LFAs) offer efficient on-site testing by simultaneously detecting multiple biomarkers from a single sample, reducing costs. In cancer diagnostics, where biomarkers can lack specificity, multiparameter detection provides more information at the point-of-care. Our research focuses on epithelial ovarian cancer (EOC), where STn-glycosylated forms of CA125 and CA15-3 antigens can better discriminate cancer from benign conditions. We have developed a dual-label LFA that detects both CA125-STn and CA15-3-STn within a single anti-STn antibody test line. This utilizes spectral separation of green (540 nm) and blue (450 nm) emitting erbium (NaYF4:Yb3+, Er3+)- and thulium (NaYF4: Yb3+, Tm3+)-doped upconverting nanoparticle (UCNP) reporters conjugated with antibodies against the protein epitopes in CA125 or CA15-3. This technology allows the simultaneous detection of different antigen variants from a single test line. The developed proof-of-concept dual-label LFA was able to distinguish between the ascites fluid samples from diagnosed ovarian cancer patients (n = 10) and liver cirrhosis ascites fluid samples (n = 3) used as a negative control. The analytical sensitivity of CA125-STn for the dual-label LFA was 1.8 U/ml in buffer and 3.6 U/ml in ascites fluid matrix. Here we demonstrate a novel approach of spectrally separated measurement of STn-glycosylated forms of two different cancer-associated protein biomarkers by using UCNP reporter technology.Graphical

An optofluidic antenna for enhancing the sensitivity of single-emitter measurements

Many single-molecule investigations are performed in fluidic environments, for example, to avoid unwanted consequences of contact with surfaces. Diffusion of molecules in this arrangement limits the observation time and the number of collected photons, thus, compromising studies of processes with fast or slow dynamics. Here, we introduce a planar optofluidic antenna (OFA), which enhances the fluorescence signal from molecules by about 5 times per passage, leads to about 7-fold more frequent returns to the observation volume, and significantly lengthens the diffusion time within one passage. We use single-molecule multi-parameter fluorescence detection (sm-MFD), fluorescence correlation spectroscopy (FCS) and Förster resonance energy transfer (FRET) measurements to characterize our OFAs. The antenna advantages are showcased by examining both the slow (ms) and fast (50 μs) dynamics of DNA four-way (Holliday) junctions with real-time resolution. The FRET trajectories provide evidence for the absence of an intermediate conformational state and introduce an upper bound for its lifetime. The ease of implementation and compatibility with various microscopy modalities make OFAs broadly applicable to a diverse range of studies.

A Novel Approach to Evaluating Crosstalk for Near-Infrared Spectrometers

Multi-channel and multi-parameter near-infrared spectroscopy (NIRS) has gradually become a new research direction and hot spot due to its ability to provide real-time, continuous, comprehensive indicators of multiple parameters. However, multi-channel and multi-parameter detection may lead to crosstalk between signals. There is still a lack of benchmarks for the evaluation of the reliability, sensitivity, stability and response consistency of the NIRS instruments. In this study, a set of test methods (a human blood model test, ink drop test, multi-channel crosstalk test and multi-parameter crosstalk test) for analyzing crosstalk and verifying the reliability of NIRS was conducted to test experimental verification on a multi-channel (8-channel), multi-parameter (4-parameter) NIRS instrument independently developed by our team. Results show that these tests can be used to analyze the signal crosstalk and verify the reliability, sensitivity, stability and response consistency of the NIRS instrument. This study contributes to the establishment of benchmarks for the NIRS instrument crosstalk and reliability testing. These novel tests have the potential to become the benchmark for NIRS instrument reliability testing.

Dual transverse fiber tip Fabry-Perot cavities for simultaneous measurements of pressure and temperature

A fiber tip sensor based on dual transverse Fabry-Perot (FP) cavities for simultaneous temperature and gas pressure measurements is proposed, fabricated and tested. The proposed fiber tip sensor is formed by one-step polishing the end face of a microstructure fiber, which contains a hollow hole in the center and an eccentric core, to 45-degrees. The hybrid fiber tip sensor consists of a quartz cavity and a gas cavity effectively solving the problem of cross sensitivity in dual-parameter sensors. By tracking the shift of the interference spectra of the two FP cavities, simultaneous measurements of temperature and pressure is achieved. With advantages of a compact structure, high spatial resolution, simple fabrication and ability of multi-parameter detection, the sensor is suitable for use in a high temperature and high-pressure simultaneous sensing applications. Furthermore, the fabrication approach ensures consistent size of the FP cavities, making the sensor suitable for mass production.

Invited] Optimally configured multi-layer optical fiber plasmonic resonance sensor based on the orthogonal design method

A generic tool for the optimal design of multi-layer sensing structure of the optical fiber plasmonic resonance based on the orthogonal design method is proposed and demonstrated. The orthogonal design method is conducted to determine the optimal type and thickness of coating materials using a finite number of solutions. A novel three-layer sensing structure with enhanced spectral characteristic of resonance is developed to evaluate the feasibility of the orthogonal design method. The sensitivity and the figure of merit of the resonance optimized for the type and the thickness of coating materials achieve up to 3560 nm/RIU and 62.129 RIU−1, respectively. Such sensitivity is 97.7 % higher than that of the sensor with 40-nm single Au layer. Meanwhile, the efficiency of the analysis combination is increased by up to mk-2-1×100%. Our work is focused on the multi-structure parameter design of optical fiber plasmonic resonance sensors and can achieve the optimized configuration of the sensing performance. It has demonstrated the promising prospects in the flexible design of the plasmonic resonance curve and in the high-sensitivity and multi-parameter detection of the plasmonic resonance.

Retracted: Optical Fiber Multiparameter Detection and Numerical Simulation and Characteristics of Water Quality Particulate Matter Based on Single-Photon Detection Technology

Retracted: Optical Fiber Multiparameter Detection and Numerical Simulation and Characteristics of Water Quality Particulate Matter Based on Single-Photon Detection Technology

Phase 1 Study of Autologous Sirpα-Low Macrophages (SIRPant-M) Administered By Intratumoral Injection Alone or in Combination with External-Beam Radiotherapy in Patients with Relapsed or Refractory Non-Hodgkin Lymphoma (NCT05967416)

Background and Significance. While a sentinel role of macrophages in channeling immune responses has long been recognized, the opportunity to harvest, harness and deploy macrophages for therapeutic potential has been underappreciated clinically. Most currently marketed and development-stage cell therapies target a single tumor-associated antigen, permitting activation of resistance and tumor escape mechanisms that frequently lead to relapse. High rates of CRS and neurotoxicity (ICANS) associated with CAR-T therapies complicate usage, with associated product labeling that includes a Risk Evaluation and Mitigation Strategy (REMS), mandating hospitalization and post-therapy monitoring with attendant administrative burden that precludes widespread use in community-based settings. Moreover, many subtypes of lymphoma (NHL) lack a readily druggable target. The current first-in-human Phase 1 study advances a novel paradigm in cell-therapy, deploying SIRPα-depleted activated macrophages, manufactured from an autologous mononuclear apheresis (SIRPant-M). In the context of macrophages, SIRPα acts as a strong negative regulator of (i) phagocytosis and (ii) productive pro-inflammatory T cell stimulation; therefore abrogation of SIRPα-activity serves as a necessary precondition for robust neo-antigen-specific anti-tumor responses. Requiring no genetic modification, in pre-clinical models these SIRPα-depleted macrophages orchestrated an immune response that targets multiple individual-specific and tumor-unique neo-antigens in parallel. SIRPant-M elicits a multi-pronged polyclonal immune response that transforms the tumor microenvironment (TME) by fostering a pro-inflammatory milieu that provides for unencumbered and orchestrated targeting of cancer cells via both cellular and humoral effector mechanisms. Manufactured and subsequently frozen as 3 aliquots from a single apheresis, activation of macrophages is brought about by conditioning the macrophages during ex vivo culture with a proprietary cytokine cocktail (PhagoAct™) with the added effect of modulating activity of SIRPα. This combination of product attributes permits the same cell product to have potential clinical applications in both solid tumor and hematologic malignancies. While this initial Phase 1 study administers the macrophages by intra-tumoral injection (ITI), subsequent studies aim to explore IV-dosing. Study design, methods and patients. This is a multicenter open-label Phase 1 study of SIRPant-M monotherapy, with sequential cohorts receiving low [90×10 6] and high [300×10 6] ITI cell doses. Cell product is administered alone or combined with focal external-beam radiotherapy (XRT). Each cell dose is administered in 3 ITI-fractions on days 1, 3, and 5 over 1 cycle. Upon confirmation of safety as a single agent, subsequent cohorts receive cell product concurrent with focally directed radiation in three 2.5 Gy fractions (7.5 Gy total). The primary end point, Dose Limiting Toxicity, is assessed over 30 days and dose escalation is gated by a standard 3+3 dose escalation design, overseen by a Safety Monitoring Committee. The enrollment target is 12-24 DLT-evaluable patients. The study enrolls an “all comers” B- and T-cell NHL population, including systemic and cutaneous histologies (CTCL), with relapsed or progressive disease following a minimum of 2- but no maximum number of prior therapies. Minimum age is 18, with no upper age limit. Prior CAR-T, bi-specific antibody and/or autologous/allogeneic transplant is allowed after recovery from treatment-related AEs. Patients must not receive immuno-suppression for GVHD and must have at least 1 target lesion that is 1.5 to 5 cm in diameter and accessible for safe ITI, ECOG ≤ 2, life expectancy &amp;gt; 3 months, renal/hepatic/coagulation parameters and blood counts that are standard for Phase 1 studies at baseline. Secondary and Exploratory Endpoints. Tumor response, including abscopal response, is evaluated by Lugano criteria or other Workgroup criteria as appropriate for the tumor type at the end of the DLT-period (Day 30), Week 12 and per SOC thereafter. Serial blood samples and a tumor biopsy before and 16 days after treatment are collected for multi-parameter analyte detection including pro-inflammatory cytokines, multiplex flow cytometry, scRNA sequencing, and ctDNA analysis to investigate pharmacodynamics and mechanism of action.