Testicular germ cell tumour regression is a rare phenomenon, where the primary testicular tumour spontaneously regresses, typically with metastatic disease at presentation. We present a case of a regressed germ cell tumour (GCT) in a 44-year-old post-pubertal male. Initially treated for suspected infection, the patient's testicular swelling prompted further investigation, leading to a radical orchidectomy that revealed the unusual histomorphologic findings of an entirely necrotic, non-seminomatous GCT consistent with a pure embryonal carcinoma. The World Health Organization classifies testicular tumours into germ cell tumours (GCT) derived from germ cell neoplasia in situ (GCNIS), GCT unrelated to GCNIS, sex cord-stromal tumours, and tumours of the testicular adnexa .A rare type of GCT derived from GCNIS is the regressed or ‘burned out’ GCT, which is a primary testicular GCT that spontaneously regresses even if, typically, there is metastatic disease at presentation .Regression can occur in all types of testicular GCT, although it is most frequently seen in seminomas where the regressed tumour is replaced by a discrete fibrous nodule or scar .We present a non-metastatic regressed non-seminomatous embryonal carcinoma GCT in a post-pubertal male.A 44-year-old, fit and well, man presented with a four-day history of a firm tender left testicular swelling. This was initially treated as orchitis with antibiotics, and an ultrasound scan (USS) of the testes was arranged as a follow-up. Testing for sexually transmitted infections was not conducted in accordance with the patient's preferences.Two weeks later, a Doppler ultrasound  meeting, which suggested a repeat USS Figure . This, iIn light of the new imaging, the case was re-discussed at the uro-radiology MDT meeting, which advised offering radical orchidectomy for histology and staging CT chest, abdomen, and pelvis.Additional preoperative investigations included serum tumour markers, which were within the normal range; LDH (lactate dehydrogenase) 493 iu/L , AFP  10 ku/L , and B-HCG (beta human chorionic gonadotropin) <1 iu/L .A staging contrast-enhanced CT of the chest, abdomen, and pelvis was conducted to assess the presence of metastatic disease. This showed a 2 mm round right apical lung nodule of indeterminate significance. Otherwise, there were no other significant findings. The patient underwent an uneventful left radical orchidectomy without the insertion of a prosthesis, followed by an uncomplicated postoperative recovery. Postoperatively, the case was discussed at the uro-oncology MDT meeting to review the histology. The MDT meeting also advised interval chest CT in three months for lung nodule follow-up and referral for regional testis MDT meeting discussion. Histopathology revealed that the entire testis was replaced by a solid well-circumscribed nodule with a tan-coloured cut surface and occasional haemorrhagic areas, where there was no viable tumour. On microscopy, the nodule described was processed in its entirety where it was composed of necrotic tissue with foci of haemorrhage, with a peripheral rim of hyalinised fibrosis mixed with macrophages and chronic inflammatory cells. The surrounding seminiferous tubules show atrophy, and there is focal GCNIS. The epididymis shows patchy foreign body type inflammation within the stroma. Immunohistochemical (IHC) stains showed that most of the necrotic cells within the nodule expressed Oct-3/4 and CD30, although staining for CD117, AFP, and HCG stains was negative, supporting a non-seminomatous embryonal carcinoma. The tumour was staged as pT1 with GCNIS present within the limits of the absence of a viable tumour.In summary, the appearances were in keeping with a regressed germ cell tumour, with evidence supporting non-seminomatous embryonal carcinoma. The presence of other non-seminomatous and seminomatous components cannot be eliminated. There is no evidence of spread outside of the testis or lymph-vascular invasion and the spermatic cord and epididymis appear clear.Regional testis MDT meeting recommended offering surveillance with interval examination and cross-sectional imaging.Moreover, interval chest CT at three months and nine months showed regressing appearances of the lung nodule, which was deemed to not be for further surveillance after a review by the respiratory physicians.A literature review shows that pure seminoma is considered the most common subtype in regressed GCTs. This is thought to be primarily because of its prevalence among testicular GCTs, rather than a specific inclination for regression in seminoma -5. This It has been stressed that even small scars should be thoroughly examined for GCT regression, as they can be easily overlooked. Patients with clinical evidence of GCT but negative sampling should consider the possibility of a regressed tumour in the opposite testis or an extragonadal primary .Additionally, patients with regressed GCT may also experience reduced spermatogenesis and testicular microlithiasis. Distinguishing between primary and secondary neoplasms is crucial when dealing with extragonadal germ cell tumours, particularly retroperitoneal ones, emphasizing the importance of comprehensive testicular assessment. Metastatic findings from ‘burned-out’ tissue have a prognosis similar to primary testicular germ cell tumours .In 2006, Balzer et al. found that the presence of intratubular germ cell neoplasia unspecified (IGCNU), now called focal germ cell neoplasia in situ, is the most specific indicator of regression in germ cell tumours within scarred testes, even without known metastatic GCT. Another relatively specific sign of GCT regression is the presence of coarse, irregular intratubular calcifications related to regressed intratubular embryonal carcinoma. Care must be taken not to confuse these with smaller, round calcifications found in atrophic tubules [In cases without IGCNU/GCNIS or coarse calcifications but displaying signs of regression, additional features such as numerous small vessels within the scarred area, clusters of Leydig cells, atrophic seminiferous tubules, and a lymphoplasmacytic infiltrate support the diagnosis of GCT regression . In thisOther tumours where spontaneous regression (SR) can be observed  are renal cell carcinoma and melanoma. It was suggested that SR factors are linked to immune responses and blood supply disruption, with activated immune response likely being a primary trigger and as the testes are typically an immunoprivileged site, immunological anti-tumour responses may be one reason why GCTs are more prone to SR ,7.Ultrasound examination typically reveals residual tumour scars with varying sonographic appearances .Orchidectomy is often required for histological confirmation and removal of potentially viable tumour cells that may not be fully treated by systemic chemotherapy, reducing the risk of tumour relapse. Spontaneous tumour regression in burnt-out testicular tumours may be because of factors such as a tumour outgrowing its blood supply, immunological reactions, and elimination ,3,5.In conclusion, germ cell tumour regression, defined as the partial or complete disappearance of tumour with or without evidence of metastatic spread, is an important phenomenon that urologists and pathologists along with other members of the multidisciplinary team should be aware of.Recognizing this phenomenon clinically, radiologically, and pathologically will enhance the management of these cases and ultimately benefit patient outcomes.


Realistic fluid models play an important role in computer graphics applications. However, efficiently reconstructing volumetric fluid flows from monocular videos remains challenging. In this work, we present a novel approach for reconstructing 3D flows from monocular inputs through a physics-based differentiable renderer coupled with joint density and velocity estimation. Our primary contributions include the proposed efficient differentiable rendering framework and improved coupled density and velocity estimation strategy. Rather than relying on automatic differentiation, we derive the differential form of the radiance transfer equation under single scattering. This allows the direct computation of the radiance gradient with respect to density, yielding higher efficiency compared to prior works. To improve temporal coherence in the reconstructed flows, subsequent fluid densities are estimated via a coupled strategy that enables smooth and realistic fluid motions suitable for applications that require high efficiency. Experiments on synthetic and real-world data demonstrated our method’s capacity to reconstruct plausible volumetric flows with smooth dynamics efficiently. Comparisons to prior work on fluid motion reconstruction from monocular video revealed over 50–170x speedups across multiple resolutions. Realistic fluid flow reconstruction is of paramount importance for a wide range of applications, including those related to special effects in film and video, artistic design, and digital media generation. However, this task poses significant challenges. On the one hand, fluid phenomena are ubiquitous in daily life, and people have high expectations for the quality of their rendering in artistic and media contexts. However, existing methods that attempt to reconstruct fluid motion through a combination of physics-based constraints and density estimation require tens of minutes per frame for reconstruction, rendering them unsuitable for interactive rendering applications.To reconstruct fluid motion, existing computed tomography (CT) methods e.g., ,2) rely  rely 2])Differentiable rendering has been a major focus in computer graphics recently. It comprises techniques that integrate rendering into end-to-end optimization by obtaining useful derivatives of the rendering process. However, integrating differentiable rendering into fluid reconstruction frameworks poses a huge challenge due to the complexity and nonlinearity of the relation between pixel intensities and fluid density. Franz et al.  proposedTo improve the efficiency of fluid reconstruction, we propose a physics-based differentiable rendering framework that analytically computes radiance derivatives with respect to density. Unlike prior automatic differentiation techniques, which have inherent computational overhead, our method directly calculates derivatives by deriving a differential form of the radiance transfer equation under single-scattering assumptions. This analytical approach avoids redundant operations and gradient tracking, significantly accelerating fluid density optimizations compared to previous differentiable rendering techniques.An efficient physics-based differentiable rendering framework is proposed for fluid density reconstruction, which is more efficient than previous models.The differential form of the Radiative Transfer Equation (RTE) based on single scattering is derived.The transport constraints and the differentiable rendering step are coupled for fluid density updating, achieving smooth fluid motion reconstruction.Furthermore, we couple our optimized renderer with a constrained density and velocity estimation strategy. By propagating velocities and densities across time steps while enforcing physical constraints, we achieve temporally coherent fluid reconstructions far more efficiently than the costly tomographic methods used previously. Our major contributions are summarized as follows:Density reconstruction: Reconstructing fluid density from 2D observations has been a popular research topic in computer graphics. Computed tomography (CT) methods, originally developed for medical applications [ications , are widIhrke and Magnor  proposedMost of these methods often required a difficult calibration step, and the reconstruction quality dropped with the decrease in the number of views. Our method focuses on reconstructing fluid density from monocular video, offering distinct advantages, including reduced costs, a drastically simplified setup, and eliminating tedious procedures like camera calibration and synchronization.Velocity reconstruction: Reconstructing fluid motion from captured videos is more challenging than reconstructing volumetric density, as motion is indirectly observed by tracing temporal changes in density. Two families of techniques exist for estimating the velocity field of a fluid: tracer-based and tracer-free approaches. Tracer-based approaches introduce tracers, such as particles or dye, into the fluid, and then the fluid velocity can be retrieved by tracing these tracers. Various PIV methods, including tomographic PIV [phic PIV , synthetphic PIV , structuphic PIV ,12,13, aphic PIV ,15, are phic PIV ,11. Thouphic PIV ,11 requiphic PIV ,17, use Visible-light-capturing is an alternative approach for fluid motion reconstruction. Corpetti et al.  used optDifferentiable rendering: Differentiable rendering is a technique that allows for the computation and propagation of derivatives of scene parameters through images. This technique has a wide range of applications, including solving analysis-by-synthesis problems and training machine learning pipelines incorporating forward-rendering processes. Loper and Black [OpenDR, which approximates the backward pass of the traditional mesh-based graphics pipeline and has inspired several follow-up works [Neural Renderer, an approximate gradient for rendering a mesh that enables the integration of rendering into neural networks. Instead of approximating the backward pass, some methods approximate the rasterization of the rendering process, enabling the computation of useful gradients. Liu et al. [Soft Rasterizer, which provides an accurate soft approximation of the standard rasterizer. Although these approximation methods reduce rendering time, generating photorealistic images containing complex interactions of light, geometry, and materials becomes difficult. Li et al. [nd Black  introducup works ,25,26,27i et al.  proposedRecently, there has been a focus on improving the efficiency of volumetric differentiable rendering. Nimier-David et al.  introducdifferentiable rendering component (coupled density and velocity estimation component (As illustrated in omponent  and the omponent . The pridifferentiable rendering component (Lines 2–3). Here, t within the input video sequences, where coupled density and velocity estimation component (Line 5), which ensures that the fluid flows adhere to the underlying physical priors. Next, given the estimated density Algorithm 1: Fluid motion reconstructionDrawing from Algorithm 1, we will now expound on how our framework operates. Initially, we take a sequence of monocular fluid images Reconstruction and CoupleEstimation algorithms. The Reconstruction algorithm reconstructs density fields from input images by leveraging our proposed differentiable renderer, to render images and compute derivatives. Equations (1)–(5), introduced in    To provide an overview of our algorithms and their relations to the formulas presented in each subsection, we include a schematic diagram in Algorithm 2: Differentiable rendererAlgorithm 3: Density reconstructionAlgorithm 4: Coupled density and velocity estimationAlgorithm 5: Velocity reconstructiont − 1 and t − 2 to t while enforcing key physical constraints. Since it takes density fields as input, Algorithm 4 calls Algorithm 5 (velocity reconstruction) to estimate velocity fields from the previous two time steps’ density fields to perform advection. Velocity reconstruction is formulated as an optimization problem with Equations (11)–(13) (t − 1 to t. This procedure couples the reconstruction of densities and velocities in a physics-constrained manner for robust fluid motion estimation.Algorithm 4 (coupled density and velocity estimation), introduced in 11)–(13)  as constFurther technical details concerning our proposed differentiable rendering framework and the coupled density and velocity estimation will be discussed below.We assume that the single-scattering model is sufficient for rendering the rough shape of the fluid volume. Therefore, we ignore the radiance contribution of multiple-scattering radiance and emitted radiance.Our method is limited to pure volume scenes, which reduces the complexity of derivative computation caused by visibility.A fluid is a participating medium that can scatter or absorb light, altering its direction and intensity as it passes through. Modeling the behavior of light in a fluid can be difficult and computationally expensive, especially when multiple scattering events are involved. Many studies have addressed these challenges by assuming simplified lighting conditions or uncluttered backgrounds in the fluid reconstruction process. This approach helps minimize interference with accuracy. Our work follows this trend and posits the following hypotheses as a result:We now depict the technical details of our differentiable rendering framework. First, we introduce the participating media rendering based on single scattering . We thenx with the total radiance x along direction x along the direction In order to lay the foundation for differentiating the radiative transfer equation (RTE), we will briefly review light transport in participating media and introduce the RTE based on the single-scattering model. When light passes through a participating media, it is attenuated along the direction x as x to the volume boundary points x to Let us denote the volume density of the participating medium at position To compute xel grid:JssThe necessary formulas for forward rendering have been introduced. In the following section, we will derive the differential form of the RTE. This form can be integrated into the differentiable rendering process to calculate the derivative of the RTE directly.Here, we introduce the differentiation of the RTE based on the single-scattering model for computing the density derivative. The differentiation of Equation  can be eSince our work only focuses on the fluid reconstruction task, the derivative Derivation of . As shown in Equation L˙ri,,9), appeR rays of length N. We only maintain gradients along active ray paths rather than the entire volume grid. These computational strategies, in conjunction with our analytical radiance derivatives, culminate in a highly efficient differentiable renderer, thereby facilitating fluid density optimization with enhanced computational efficacy.Furthermore, as depicted in lines 14–15, Building upon our proposed differentiable rendering framework, we present the reconstruction of the density field using our framework and provide details in Algorithm 3. We begin by computing the loss function of the target and primal images, followed by reading the density gradient from the recorded sampling positions of the generated ray. The gradients of density with respect to the loss value are computed and saved in the volume data Most previous works for fluid reconstruction directly updated the fluid density in each time step using tomographic methods from input video sequences. While this works well for systems with a large number of cameras, the reconstruction quality drops significantly when the number of cameras  reduces, making the tomography problem formulation ill-posed. To solve this ill-posed problem and improve the reconstruction quality, we apply a coupled estimated strategy, which makes the efficient reconstruction of realistic and smooth fluid flow possible. A possible solution is coupled density and velocity updating, which was developed by Eckert et al. , yet thet based on the given states of time t − 1 and time t − 2. The details of our coupled density and velocity estimation are depicted in Algorithm 4. To proceed, we first estimate velocity t − 1 and time t − 2 according to Algorithm 5. We then predict the velocity and density for the current time step t based on physical priors, i.e., the density and velocity transport over the time steps and the incompressibility of the velocity. Note that incompressibility is ensured by projecting the velocities onto the space of divergence-free velocities, called Our approach is to predict the density field depth regularization to gain control over the motion in depth. Because this regularized term breaks the sparse property of the matrix, the optimization problem cannot be solved efficiently.While the last two steps shown in lines 3–4 of Algorithm 4 are similar to those in [To improve the efficiency of velocity reconstruction, we propose a modified constraint as follows: In Equation , the firvelocity . These rk is the iteration number; f of f 12), we mEquation , where vEquation ) is solvThe process of velocity reconstruction is shown in Algorithm 5. Lines 3–5 are the PD updates, and lines 6–10 check the convergence of the iterative computation.We implemented our proposed approach using a combination of Python and C++. The differentiable renderer was developed in Python, leveraging the Taichi programming language ,37 for pThe coupled density and velocity estimation component was implemented in C++ for computational efficiency and numeric precision. We interfaced with this C++ module from the Python renderer using the pybind11 library. Pybind11 enabled us to seamlessly pass data between the Python and C++ code.We evaluated our method on a workstation with an Intel Xeon E5-2620 v4 CPU and an Nvidia GeForce RTX 2080 Ti GPU. All results and timings provided were obtained by executing the code on the GPU hardware, leveraging parallelized implementations for performance.We conducted a rigorous validation of our method through both qualitative visualizations and quantitative analyses. Our validations focused primarily on the claimed contributions of the proposed differentiable renderer and reconstruction framework. As the accuracy of the estimated gradients and computational performance are critical metrics for evaluating a differentiable renderer, we first validated these two aspects. Subsequently, we conducted ablation studies to assess the reconstruction capabilities of our differentiable renderer and the efficacy of the transport constraints. Furthermore, given the significant impact of the estimated velocity on reconstructed fluid motions, we analyzed comparisons between our velocity estimates and the ground-truth data. Finally, we compared our approach against previous methods through both qualitative visualizations and quantitative efficiency metrics.Validation of gradient computation. To validate the effectiveness of our proposed differentiable renderer, we optimized a density field and analyzed the evolution of the calculated derivatives. The initial density configuration was in the shape of a rabbit, which was optimized by updating the density field based on a target smoke image. The image sequence in Initially, the density inside the rabbit shape needed to decrease, while the density in the smoke region had to increase to match the target. Since the smoke density was thinner than the rabbit density, the derivatives for the smoke density diminished faster, disappearing after around 30 iterations. In contrast, significant derivatives for the rabbit density persisted from iterations 0 to 50. By iteration 99, the optimization had converged to the target image. Overall, Performance validation of our differentiable renderer. Since our differentiable renderer significantly differed from previous methods based on differential volumetric path tracing in implementation, different factors impacted its performance. Previous physics-based differentiable renderers heavily relied on the Monte Carlo method to estimate the radiance and its derivatives. Hence, these methods’ performance was affected by the number of samplings. Unlike these methods, the volumetric data size significantly impacted our renderer’s performance. To characterize this relationship, validations were performed on the rabbit scene in The memory usage of our differentiable renderer was another essential aspect of its performance. Similar to the runtime analysis, we observed a direct correlation between the resolution of the volumetric data and the GPU memory usage. As the resolution increased, so did the memory requirement. The memory usages for the resolutions Evaluation of density reconstruction. To evaluate the reconstruction accuracy of our proposed method, we conducted an experiment using synthetic fluid motion data. The ground-truth fluid flows were generated using the Mantaflow simulator [Mitsuba 3 [coupled density and velocity estimation component. Qualitatively, the physically constrained result in imulator . The denitsuba 3 . This syEvaluation of the velocity estimation. The evaluation of the velocity estimation is of utmost importance in reconstructing fluid motions, as it significantly impacts the reconstruction quality and temporal consistency of fluid motions. We compared estimated velocity fields obtained from reconstructing Comparison to previous work. While we demonstrated our method’s fluid motion reconstruction capabilities above, further comparative evaluations were essential to fully validate its abilities against previous approaches. To this end, we conducted fluid motion reconstruction from the same initial configuration using both our method and Franz et al.’s approach [approach . Our metFurthermore, run-time efficiency is an important indicator to evaluate a reconstruction framework. To validate the efficiency of our proposed framework, we compared the average runtime of our method against Franz et al.’s method for reconstructing fluid densities from video inputs. As shown in For the 64 × 96 × 64 resolution, our complete reconstruction time per frame was 6.13 s, over 59× faster than Franz et al.’s 363 s. More significantly, our differentiable rendering time was just 0.08 s, demonstrating a speedup of over 870× compared to their 69.6 s for this key computational stage.For the higher resolutions of 128 × 192 × 128 and 256 × 288 × 256, our method outperformed Franz et al.’s by factors of approximately 172 and 173, respectively, in terms of average reconstruction time. Furthermore, our differentiable rendering stage exhibited speedup factors of around 2655 and 1676 compared to Franz et al.’s methodology.Mitsuba 3 [Reconstructing fluid flows from real-world video captures presents significant challenges due to ambient interference and computationally intensive processing requirements. Previous approaches have required several minutes per frame for reconstruction, severely limiting applicability in interactive contexts. Our proposed method aimed to address this limitation by enabling the efficient modeling of fluid motions from monocular videos of real fluids. To validate the practical applicability of our method, we reconstructed fluid motions from a monocular video capturing real fluid flows from a fixed viewpoint. As depicted in itsuba 3  from a pWe introduced a novel method to efficiently reconstruct fluid density fields from monocular video data. The key contribution was our newly proposed efficient differentiable rendering framework for participating media and the improved transport constraints. Our approach outperformed previous methods by considering both computational efficiency and visual quality. Looking ahead, worthwhile future work includes reducing current limitations, such as incorporating the differentiable rendering of surface models and developing advanced sampling strategies to further improve efficiency. Overall, this work represents an important advance in performing monocular video-based fluid reconstructions, providing a valuable new tool for digital content creation.


A magnetorheological fluid (MR fluid) is mainly composed of soft magnetic particles, surfactants, and the base carrier fluid. Among these, soft magnetic particles and the base carrier fluid influence the MR fluid significantly in a high-temperature environment. Therefore, a study was carried out to investigate the changes in the properties of soft magnetic particles and base carrier fluids in high-temperature environments. On this basis, a novel magnetorheological fluid with high-temperature resistance was prepared, and the novel magnetorheological fluid had excellent sedimentation stability, of which the sedimentation rate was only 4.42% after heat treatment at 150 °C followed by one-week placement. At 30 °C, the shear yield stress of the novel fluid was 9.47 kPa under the magnetic field of 817 mT: higher than the general magnetorheological fluid with the same mass fraction. Moreover, its shear yield stress was less affected by the high-temperature environment, reducing by only 4.03% from 10 °C to 70 °C. The novel MR fluid can be applied to a high-temperature environment, effectively expanding the application range of MR fluid. Magnetorheological (MR) materials are a significant branch of intelligent materials which make continuous and nonpolar reversible changes under the action of a magnetic field. MR fluids mainly comprise soft magnetic particles, surfactants, and the base carrier fluid ,2,3,4,5.Currently, MR fluid, the most widely studied and applied MR material, is commonly used in active vibration control ,4,5,6,7,In order to solve the above issues, many scholars have conducted a great deal of research on the structure of magnetorheological fluid transmission devices to enhance the heat dissipation capability of the devices themselves. Wang et al.  designedHowever, fewer scholars are conducting research based on the high-temperature characteristics of the components of MR fluids to improve the overall high-temperature stability of the fluids. In this work, the magnetic properties and high-temperature oxidation of soft magnetic particles in a high-temperature environment were analyzed, and the viscosity, thermal evaporation, and thermal expansion properties of the base carrier fluids under a high-temperature environment were analyzed. The MR fluid with excellent high-temperature stability was studied by selecting high-performance materials, and its various properties were tested. This work provides an excellent MR fluid for MR devices in high-temperature conditions, which can enhance the application prospects of MR fluid.The magnetic properties of soft magnetic particles are the main reason for the unique rheological effect of MR fluids. In a common preparation process, micron-sized carbonyl iron powder (CIP) is often used as a source of soft magnetic particles to prepare MR fluid, due to its simple preparation, low price, high purity, and fine particle size. However, the high-temperature stability and shear yield stress of magnetorheological fluids prepared by CIP make it challenging to meet the usage requirements. It has been found that doping a small amount of soft magnetic nanoparticles in micron-sized CIP particles can effectively improve the sedimentation stability and shear yield stress of MR fluid . FurtherThe MPMS 3 by QUANTUM DESIGN (America) was applied to measure the magnetic properties of the micro-nano composite system and CIPs in a high-temperature environment. As shown in Moreover, it can be seen from The expansion, evaporation, and viscous temperature characteristics of the base carrier fluid significantly impact the performance of MR fluid in a high-temperature environment. In this work, the six different types of high-temperature resistant base carrier fluids in The SNB-1T digital rotational viscometer by FANGRUI (China) and the digital display thermostatic oil bath were applied to measure the viscosity–temperature characteristics of the base carrier fluids in As shown in When the temperature rises, the arrangement of molecular spacing within the fluid is damaged, the kinetic energy between fluid molecules increases, the molecular spacing becomes more significant, the internal friction resistance decreases, and the viscosity of the liquid decreases. The viscosity index is commonly used to describe the degree to which the viscosity of a fluid changes with temperature. The higher the viscosity index, the less the viscosity of the fluid is affected by temperature. The viscosity indices of the six samples can be obtained from RSF-102, FL310, and Castor oil have dynamic viscosities of 4.07 Pa·s, 2.08 Pa·s, and 1.248 Pa·s at 20 °C, respectively. The dynamic viscosities of these base carrier fluids are relatively high, which should be discussed further with subsequent experiments.V1 and V2 are the volume of the liquid at temperatures T1 and T2, respectively, as can be seen in The thermal expansion property of base carrier fluids refers to the phenomenon that the volume of the fluids expands with the increasing external temperature under constant external pressure. The volume expansion coefficient is often used to characterize the expansion properties of liquid substances, and can be represented as−3/°C in the range of 10 to 200 °C.It can be seen from evW is the recorded weight after heating and oW is the original weight before heating.The expansion rate of base carrier fluids can be obtained from Equation (2),It can be seen from The content of the above research is summarized in The preparation process of MR fluids is shown in According to the previous study, two formulations of MR fluids were prepared and placed under different working conditions to measure their sedimentation rates. The specific formulations of MR fluids are shown in As shown in The variation of the sedimentation stability for Sample B is quite interesting. At room temperature, the sedimentation rate of Sample B remained constant after three days. Multiple experimental verifications revealed that the upper part of Sample B formed an odorless solidified black colloid with time, leading to the inability to observe its sedimentation rate. Additionally, the high-temperature conditions accelerated this chemical reaction, resulting in the sedimentation rate of Sample B in working condition 4 and working condition 6 being 0%.Hydroxy silicone oil reacts chemically with some surfactants at room temperature, causing the liquid to form a colloid. High-temperature conditions can provide a better catalytic effect for this chemical reaction. In this study our aim was to prepare a high-temperature-resistant MR fluid for transmission equipment. Hence, formulation B is unsuitable.Sample A and dimethyl silicone oil were measured in a high-temperature environment of about 250 °C for 4 h.As shown in Zero-field viscosity is an essential indicator in MR fluid transmission. However, it decays considerably at high temperatures. Therefore, a comparative test was conducted to analyze the effect of CIPs and Fe-Co-Ni nanoparticles on the viscosity–temperature characteristics of MR fluids without changing other parameters in the formulation and only changing the components of soft magnetic particles. The effect of CIPs and Fe-Co-Ni nanoparticles on the viscosity–temperature properties of MR fluids was analyzed by a comparative test.It can be seen from A comparison group was also set up to analyze the trend of high-temperature performance of the novel MR fluid. The comparison group formulations of Sample C are composed of sodium lauryl phosphate (1.5 wt%), complex MES (1.5 wt%), ethylene glycol monostearate (1.5 wt%), glycerol monostearate (1.5 wt%), hydrophobic pyrogenic silica (1.5 wt%), CIPs (40 wt%), and dimethyl silicone oil (53.5 wt%).The SNB-1T digital rotational viscometer by FANGRUI (China) was applied to measure the temperature–viscosity properties of Sample A and Sample C.The variation pattern of the viscosity–temperature curve for MR fluids is similar to that of the base carrier fluid. At the same time, it can be seen from The rotational rheometer MCR 301 equipped with MRD 180 by ANTON PAAR (Austria) was used to obtain the rheological curves of Sample A and the general MR fluid (Sample C). The Herschel–Bulkley model with better fitting effects [At 30 °C, the yield stress of Sample A was sharply enhanced before 500 mT, but the increase decreased after reaching a specific value. Sample A and Sample C both reached the limit at 817 mT with 9.47 kPa and 7.23 kPa, respectively. The shear stress of Sample A was about 131% that of Sample C. This experiment proves that the micro-nano composite system could effectively enhance the shear yield stress of the MR fluid.The effect of temperature on shear yield stress is shown in From the above analysis, it is clear that the properties of soft magnetic particles mainly influence the yield stress of MR fluids. The MR fluid comprising the micro-nano composite system has better yield stress.In order to observe the microscopic manifestation of the rheological effect of magnetorheological fluid and the time response characteristics, a high-speed photomicrographic imaging test bench was established, as shown in In this work, the properties of soft magnetic particles and base carrier fluids for MR fluids were investigated in a high-temperature environment. The micro-nano composite system and dimethyl silicone oil show an excellent performance at high temperatures. The micro-nano composite system was composed of CIPs supplied by TIANYI (China) and Fe-Co-Ni supplied by QIYUE (China), and its mass fraction was 40 wt%. The surfactants and thixotropic agents were sodium lauryl phosphate (1.5 wt%), complex MES (1.0 wt%), ethylene glycol monostearate (1.5 wt%), glyceryl monostearate (1 wt%), and hydrophobic fumed silica (1.0 wt%). The base carrier fluid was 100 cSt dimethyl silicone oil. According to above formulation, a novel MR fluid for high temperatures was prepared and its sedimentation stability, expansion rate, volatilization rate, and temperature–viscosity property, as well as shear yield stress were investigated at high temperatures. In the experiments, the novel MR fluid had better sedimentation stability and higher shear yield stress.


Streptococcus pneumoniae (iSpneumo) and Streptococcus pyogenes (iGABHS) have substantial morbidity and mortality. Decrease in culture (Cx) proven iSpneumo during COVID has been reported. We used PCR in empyema fluid for enhanced SBI microbiologic diagnosis. Here, we evaluate Cx/PCR diagnosed community acquired SBI (CA-SBI) in children and relationship with Flu burden and social distancing.Association of serious bacterial infections (SBI) and preceding respiratory viral illness (RVI) has been described. Social distancing, (masking and lockdowns), in response to pandemic resulted in > 95% decrease in RVI, specifically influenza (Flu). Invasive Data from surveillance of bacteremia and CA-empyema (Cx and PCR) at our institution was used to identify CA-SBI cases in children 3 months – < 18 years. Spinal fluid Cxs were reviewed to identify meningitis cases. We used data from the Orange County Health Care Agency for detection of countywide Flu trends. We normalized yearly CA-SBI cases per 10,000 discharges, grouped them into before COVID (BC) (7/1/2017 – 12/31/19) and after covid (AC) (1/1/2020 – 6/30/2022), and compared to countywide Flu cases 7/1/2017 – 6/30/2022.S aureus  and E coli  were most common overall  and per cohort  respectively ; 35.7% and 12.9% of iSpneumo and iGABHS respectively were identified by PCR only. Both decreased during COVID . iSpneumo and iGABHS mortality was 3.6% and 12.9% respectively. There were no iSpneumo (5/2020 – 10/2021) or iGABHS 12/2020 – 11/2021) cases or deaths when Flu was not circulating.We identified 361 CA-SBIs. iSpneumo and iGABHS cases decreased during social distancing, which included mandatory masking. No cases or deaths occurred when Flu was not circulating supporting association with Flu. Decrease in iSpneumo by routine pediatric vaccination has limitations due to differential protection by serotype and serotype replacement. Seasonal masking should be evaluated to decrease CA-SBI associated pediatric morbidity and mortality due to iSpneumo and iGABHS, further Flu vaccine development is needed.Antonio C. Arrieta, MD, FIDSA, FPIDS, Astellas Pharma Global Development, Inc.: Advisor/Consultant|Astellas Pharma Global Development, Inc.: Grant/Research Support|Astellas Pharma Global Development, Inc.: Honoraria|Cumberland Pharmaceutical: Grant/Research Support|IDbyDNA: Advisor/Consultant|IDbyDNA: Grant/Research Support|Melinta: Grant/Research Support|Merck: Advisor/Consultant|Merck: Grant/Research Support|Nabriva: Grant/Research Support|Paratek Pharmaceuticals: Grant/Research Support|Pfizer, Inc: Advisor/Consultant|Pfizer, Inc: Grant/Research Support|Roche/Genentech: Grant/Research Support|The Medicine Company: Grant/Research Support Delma Nieves, MD, Merck: Grant/Research Support|Summit Therapeutics: Grant/Research Support Negar Ashouri, MD, Merck: Grant/Research Support


ENHO) gene and widely present in liver, pancreas, heart, kidney, brain, and vascular tissues. Abnormal adropin is associated with metabolic, inflammatory, immune, and central nervous disorders. Whether adropin is involved in the development of colorectal cancer (CRC) is still unclear. Here, decreased adropin expression of tumor-nest cells in advanced-stage CRC was demonstrated. Adropin expressed by carcinoma cells was negatively correlated with macrophage infiltration in the matrix of CRC tissues. However, tumor macrophages enhanced adropin expression and were positively correlated with tumor invasion and metastasis. ENHO gene transfection into colon cancer (MC38) cells inhibited tumor growth in vivo, accompanying the increase of M1 macrophages. Treatment with low-dose adropin (< 100 ng/mL) on macrophages ex vivo directly increased mitochondrial reactive oxygen species for inflammasome activation. Furthermore, ENHO−/− mice had less M1 macrophages in vivo, and ENHO−/− macrophages were inert to be induced into the M1 subset ex vivo. Finally, low-dose adropin promoted glucose utilization, and high-dose adropin enhanced the expression of CPT1α in macrophages. Therefore, variations of adropin level in carcinoma cells or macrophages in tumor tissues are differently involved in CRC progression. Low-dose adropin stimulates the antitumor activity of macrophages, but high-dose adropin facilitates the pro-tumor activity of macrophages. Increasing or decreasing the adropin level can inhibit tumor progression at different CRC stages.Adropin is encoded by the energy homeostasis-associated (The online version contains supplementary material available at 10.1186/s12885-023-11519-5. ENHO) gene, including a secretory signal peptide (amino acids 1–33) and a biologically active fragment (amino acids 34–76). Humans, mice, and rats share the same amino acid sequence. Adropin plays a crucial role in modulating glucose and fatty acid metabolism [Adropin is a peptide hormone with 76 amino acids MW: 4.499 kDa) encoded by the energy homeostasis-associated  in adipose tissues and the liver to inhibit pre-adipocyte differentiation into mature adipocyte and thus reducing fat accumulation and macrophage infiltration-related inflammation . On the Colorectal cancer (CRC) is the third popular type of cancer worldwide. Most core metabolic pathways, including glucose, glutamine, amino acid, and lipid metabolism, substantially vary in CRC cells , 15. Methttps://portal.Gdc.Cancer.gov), samples of 51 normal individuals and 646 tumor patients were collected for the analyses of ENHO and GPR19 gene expression (level 3 HTSeq-FPKM), immune system infiltrates, and related clinical information. All patients with CRC (n = 644) were divided into two groups according to adropin level and GPR19 expression. R language (version 3.6.3) was used to analyze ENHO and GPR19 mRNA data and clinical features. TNM stage was classified following the 8th edition (2017) of TNM Classification for CRC by the American Joint Committee on Cancer. The survival of patients with CRC with different adropin and GPR19 expression was analyzed by Kaplan–Meier (K-M) survival analysis.Based on The Cancer Genome Atlas  aged 31–82 years old with an average age of 62.7 years were collected from the Affiliated Hospital of Yangzhou University. Normal issues surrounding the tumor tissues (5 cm away from tumor tissues) were collected as the control. All tumor tissues were confirmed as adenocarcinoma by two independent pathologists. The clinical features of the patients are listed in Supplementary Table A lentivirus vector system was purchased from GeneChem . Recombinant adropin was purchased from Signalway Antibody . Recombinant IFN-γ was from Absin , TGF-β1 (7666-MB-005) was from R&D Systems , IL-4 (HY-P70653) and IL-10 (HY-P70517) were from MedChem Express , and LPS (L2654) was from from Merck. ENHO-deficient mice with C57BL/6 background were generated in GemPharmatech  and routinely bred in the Center for Comparative Medicine of Yangzhou University. All animal experiments were approved by the Institutional Animal Care and Use Committee of Yangzhou University .The antibodies used for immunohistochemistry were as follows. Adropin (ab224725) was from Abcam ; GPR19 (Orb161223) was from Biorbyt ; CD68 (66231-2-IG), arginase 1 , and PD-L1 (66248-1-IG) were from Proteintech ; and antibody (MA5-17139) against inducible nitric oxide synthase (iNOS) was from Invitrogen .The antibodies for Western blot were as follows. Adropin (NBP1-26387) was from Novus . NLRP3 (D4D8T), caspase-1 (E2Z1C), IL-1β (D3U3E), HK2 (C64G5), C/EBPβ (D56F10), and actin (3H6G5) were from Cell Signaling Technology . ARG1 (66129-1-IG), iNOS (MA5-17139), and GLUT1 (66290-1-IG) were from Proteintech . CPT1α (EPR218–43-71-2 F) and PPARγ (Ab23673) were from Abcam .The following antibodies were used for flow cytometry and sourced from eBioscience, Biolegend, and BD Pharmingen: CD11b (M1/70), F4/80 (BM8 or T45-2342), CD16/32 (B335358), CD206 (C068C2), CD86 (GL-1), CD80 (11-0801-82), CD3 (145-2C11), CD8a (53 − 6.7), and IL-1β (12-7114-82).All biopsies were fixed in 10% neutral buffer formalin overnight, embedded in paraffin, and cut into sections. After antigenic epitopes were retrieved, the sections were routinely incubated with primary antibody overnight and stained with peroxidase-conjugated or fluorescein-conjugated secondary antibody. Finally, the sections were stained, observed under a high-power optical microscope, and evaluated .Spleen single-cell suspension were obtained by grind, cracking and centrifugation.Splenic macrophages were isolated from spleen single-cell suspension using Anti-F4/80 MicroBeads UltraPure and then cultured in complete culture medium  in a humidified incubator with 5% CO2 at 37 °C. The macrophages were polarized into M1 in the presence of 100ng/mL LPS and 20ng/mL IFN-γ(20ng/mL) for 24 h,or into M2 by adding IL-4(50ng/mL) or IL-10(50ng/mL) or TGF-β(25ng/mL) for 24 h. Splenic macrophages were treated with Adropin for 24 h.6) were subcutaneously injected into the left dorsal part of 8-week-old male C57BL/6 mice. Tumor diameters were monitored every 3 days. On day 20, the mice were euthanized, and tumor tissues were dissected from the mice. The tumor tissues were cut into small pieces and ground. Mononuclear cells were passed through a filter net and enriched by density-gradient centrifugation with 30% percoll solution for further analysis.MC38 cells were acquired from American Type Culture Collection.MC38 cells were transduced with the indicated ENHO-recombinant lentivirus. Then, MC38 cells with stable adropin expression were selected with puromycin (2 µg/mL). Logarithmic-phase MC38 cells  and MitoSOX Indicator  were used to evaluate the levels of cytoplasmic reactive oxygen species (cROS) and mitochondrial reactive oxygen species (mROS).Cell lysates were generated, separated by polyacrylamide gel electrophoresis, and transferred to polyvinylidene fluoride membrane. Then, the membranes were stained with primary and secondary antibodies. Imprinted signals were developed with an enhanced chemiluminiscent kit (Vazyme).t test, and comparisons of more than two groups of data were analyzed by ANOVA. Spearman correlation coefficient was used to analyze the linear correlation. All analyses were carried out using GraphPad Prism 9.0. Significance of difference was indicated by P < 0.05 (*), P < 0.01 (**), and P < 0.001 (***).Differences between two groups were analyzed by grouped student Based on the analysis by TCGA, ENHO mRNA level substantially decreased in tumor tissues Fig. A compare+ GPR19+ cells were present in the stroma of CRC biopsies than in normal tissues , but no variations in adropin+ iNOS+ cells were observed between early-stage (Dukes A-B) and late-stage CRC (Dukes C-D)Fig. F and G. ion Fig. H and I. + T cells  stimulated CD86 expression but had no obvious effects on CD80 and CD206 macrophages Fig. D. Increa+ macrophages were induced in the KO mice compared with the WT mice. Macrophages in the two groups were treated with IL-4 and showed comparable CD206 expression  and downregulating PDH kinase-4 that inhibits PDH, several −/− macrophages , as a key regulator for cell proliferation, activation, and glucose metabolism, is at the crossroads of the PI3K/Akt and AMPK signaling pathways . Phosphoges Fig. C. In addpin Fig. D in vivopin Fig. E. The re−/− mice had less M1 macrophages. The inflammasome activation in the adropin-treated macrophages was attributed to increased mROS due to increased oxidative metabolism in the mitochondria. Thus, an important role of adropin in CRC progression was addressed in this study, and adropin could be differently exploited to be a target in different CRC stages.A growing body of literature has suggested a link between obesity and cancer . AdropinTumor cells usually rely on anaerobic glycolysis to supply energy for rapid growth . Hence, Notably, adropin had dual effects on macrophages. The macrophages had increased glucose oxidation after treatment with low-dose adropin (< 100 ng/mL), but fatty acid oxidation was only enhanced under the stimulation of high-dose adropin (> 100 ng/mL). The normal plasma adropin concentration in humans is 1–10 ng/mL . For mac+ T cells were recruited into tumor tissues. We could not discriminate whether the CD8+ T cell activation was due to the direct effect of adropin or the indirect stimulation of adropin-impacted macrophages. On the one hand, how adropin directly affects effector T cell function still remains unknown. On the other hand, the loss of ENHO in individuals is associated with the loss of regulatory T cells [When MC38 cells were overexpressed with adropin and injected into mice, more CD8 T cells  and leadvia fatty acid oxidation. Considering that adropin is affected by exercise and diet, a healthy lifestyle can indeed inhibit tumor occurrence via enhancing immune surveillance.In conclusion, decreased adropin in carcinoma cells was involved in CRC progression. Low-dose adropin (< 100 ng/mL) could promote the induction of M1-like macrophages via increased glucose oxidation in the mitochondria, but high-dose adropin (> 100 ng/mL) induced M2-like macrophages Below is the link to the electronic supplementary material.Supplementary table 1-Clinical characteristics of 68 colorectal cancer patients. Supplementary table 2-Clinical characteristics of colorectal cancer patients with metastasis. Supplementary figure 1. Phenotypic markers of macrophages with the treatment of adropin detected by flow cytometry. Supplementary figure 2. IL-1β and ROS production by macrophages with the treatment of adropin detected by flow cytometry. Supplementary figure 3. IL-1β and mROS production by macrophages with the treatment of higher-dose adropin detected by flow cytometry. Supplementary figure 4. Representative results of cell markers on macrophages or CD8+T cells detected by flow cytometry. (A) Macrophages in spleens of WT or KO mice. (B) M1 or M2 cells in WT or KO mice. (C) CD86 and CD206 on WT or KO macrophages treated with LPS/IFN-γ or IL-4. (D) NKG2D, CD69, IFN-γ or granzyme B (GZB) of CD8+T cells as cocultured with WT or KO macrophages.Supplementary Material 3


Carbapenem-resistant Enterobacterales are a CDC urgent threat and need effective free drug concentrations at sites of infection such as epithelial lining fluid (ELF) for pneumonia. Therefore, it’s the goal of this study to compare efficacy of meropenem serum and ELF concentrations while measuring for susceptibility changes in a five day in-vitro pharmacodynamic model.E. cloacae with porin mutations and a meropenem minimum inhibitory concentration (MIC) of 2μg/mL was used to make a starting model inoculum of 6 log10 CFU/mL. One compartment in vitro pharmacodynamic models were run in triplicate, with inflow media set to the antibiotic half-life of 1.5 hours. Samples were taken from models for CFU/mL counts at 0, 6, 8, 24, 32, 48, 72, 96, and 120 hours with a limit of detection 2 log10 CFU/mL. Antibiotic target peak concentrations for serum was 26.6 μg/mL (71% T >MIC) to emulate free drug concentrations in patients at steady state receiving 2g every 8 hours. For ELF simulation, we targeted concentrations of 17.3μg/mL (58% T >MIC) to reflect ELF to unbound drug in plasma ratio of 0.65. MICs for susceptibility changes were determined via E-test, with samples from models at 24, 48, 72, 96, 120 hours being compared to 0-hour MICs. Bactericidal activity was defined as ≥3 log10 CFU/mL reduction in colony counts from the initial inoculum. CFU/mL counts were compared via t-test and p-values of ≤0.05 were considered significant.An AmpC β-lactamase producing Meropenem Target ConcentrationsTargeted concentrations to simulate percent time of unbound meropenem in serum and ELF above the MICSerum targeted models reached the limit of detection by 24 hours with bactericidal activity through 96 hours (p< 0.05). At 120 hours, bacterial regrowth occurred in 2/3 models but was not accompanied by increased MICs (MIC=0.5μg/mL). ELF targeted models reached the limit of detection by 48 hours for 2/3 models and had significant bactericidal activity through 72 hours (p< 0.05). Regrowth occurred at 96 hours through 120 hours and was accompanied by heterogenous resistant sub-populations (MIC shifts from 2 to 4 and to >32μg/mL). The heterogenous colony formation was first seen at 24 hours in ELF models.Meropenem Antibacterial Activity against E. cloacaeMeropenem dosing simulating serum concentrations in sick patients at steady state and in ELFWith both meropenem targeted concentrations above recommended 40% T >MIC, there was bacterial regrowth. Target site concentrations should be considered as a contributing factor to treatment failure and resistance development.jason M. Pogue, PharmD, AbbVie: Advisor/Consultant|Entasis: Advisor/Consultant|Ferring: Advisor/Consultant|GSK: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Qpex: Advisor/Consultant|Shionogi: Advisor/Consultant Kerry L. LaPlante, Pharm.D., FCCP, FIDSA, FIDP, Abbive: Advisor/Consultant|Abbive: Grant/Research Support|Ferring: Advisor/Consultant|Gilead: Grant/Research Support|Melinta: Advisor/Consultant|Merck: Grant/Research Support|NIH: Grant/Research Support|Pfizer: Grant/Research Support|Seres: Advisor/Consultant|Shionogi inc.: Grant/Research Support|VA-HR&D: Grant/Research Support


This work was partly supported by the Research Council of Norway through its Centers of Excellence funding scheme (grant number 262700)’.


Aspergillus spp. and non-tuberculous mycobacterium.Patients with pulmonary non-tuberculous mycobacteriosis (NTM) have been increasing in Japan in recent years. Furthermore, NTM cases complicated with pulmonary aspergillosis are associated with a poor prognosis. However, little is known about the interaction between A. fumigatus growth and gene expression, supernatants of M. avium (ATCC 700737) and M. abscessus (ATCC 19977) were added to A. fumigatus .To investigate the effect of NTM metabolites on A. fumigatus exposed to culture supernatant of each NTM were significantly increased compared to the control . The expression of genes involved in the synthesis of secondary metabolites of A. fumigatus, such as gliotoxin, was decreased after the exposure to supernatant by RNA sequencing analysis .The biofilms and biomass of A. fumigatus while suppressing the production of some secondary metabolites. We are now trying to reproduce this phenotype in mouse model and to identify the causative agent from NTM culture supernatant and elucidate the mechanism further.Our results suggest that exposure to culture supernatant of NTM may support the growth of Masato Tashiro, MD, PhD, Asahi Kasei Pharma Corporation: Advisor/Consultant|Asahi Kasei Pharma Corporation: Honoraria|Sumitomo Pharma Co., Ltd.: Honoraria Koichi Izumikawa, M.D., Ph.D., Asahi Kasei Pharma Corporation: Grant/Research Support|Asahi Kasei Pharma Corporation: Honoraria|Astellas Pharma Inc.: Honoraria|DAIICHI SANKYO COMPANY, LIMITED: Grant/Research Support|DAIICHI SANKYO COMPANY, LIMITED: Honoraria|KYORIN Pharmaceutical Co., Ltd.: Honoraria|Merck & Co., Inc.: Honoraria|Pfizer Japan Inc.: Honoraria|Shionogi & Co., Ltd.: Grant/Research Support|Shionogi & Co., Ltd.: Honoraria|Sumitomo Pharma Co., Ltd.: Grant/Research Support|Sumitomo Pharma Co., Ltd.: Honoraria|TAIHO PHARMACEUTICAL CO., LTD.: Grant/Research Support


Influenza remains a significant public health concern due to the limited efficacy of vaccines. Cidara has developed CD388, a multivalent conjugate of a dimeric neuraminidase inhibitor with a proprietary hIgG1 Fc domain engineered for extended half-life, currently in clinical development. Here we describe the efficacy of CD388 against a panel of geographically and temporally diverse influenza A and B subtypes in mouse prophylactic models, and against H1N1 in a SCID model.Efficacy studies were conducted in BALB/c mice lethally challenged with influenza virus. CD388 was administered intramuscularly (IM), seven days prior to challenge. Animals were monitored daily for 21 days or longer for survival (< 20% BW loss). For SCID studies, mice were dosed with CD388 two hours prior to lethal challenge with influenza A H1N1. Oseltamivir and baloxavir were included as comparators.Table 1). Daily BW measurements of treatment groups supported survival findings and showed a transient BW loss , before animals recovered weight.Across all influenza subtypes, CD388 treatment at ≤1 mg/kg resulted in 100% survival . In contrast, a single dose of CD388 at 1 mg/kg extended the median time of death to beyond Day 21. A dose response was evident at higher CD388 doses with the median time of death extended to Day 30 and 35 for 3 and 10 mg/kg groups, respectively.In SCID studies, the median time of death for vehicle treated animals was seven days. Treatment with oseltamivir  and baloxavir  at their human equivalent doses extended the median survival time to Day 10 and 16, respectively (This data demonstrated a single IM administration of CD388 fully protected animals from lethal challenge against seasonal influenza A and B. Importantly, CD388 was found to be efficacious in a severe model of immune deficiency. This data supports the prophylactic use of CD388 to prevent seasonal influenza in individuals.James Levin, PhD, Cidara Therapeutics: Stocks/Bonds Simon Döhrmann, PhD, Cidara Therapeutics: Stocks/Bonds Jason N. Cole, Ph.D., Cidara Therapeutics: Stocks/Bonds Karin Amundson, BSc, Cidara Therapeutics: Stocks/Bonds Allen Borchardt, PhD, Cidara Therapeutics: Stocks/Bonds Thomas P. Brady, Ph.D., Cidara Therapeutics: Stocks/Bonds Thanh Lam, PhD, Cidara Therapeutics: Stocks/Bonds Joanne Fortier, BSc, Cidara Therapeutics: Stocks/Bonds Amanda Almaguer, Bachelors, Cidara Therapeutics: Stocks/Bonds Leslie W. Tari, Ph.D., Cidara Therapeutics: Stocks/Bonds


Candida auris (C. auris) is a highly pathogenic, often multidrug resistant organism, that spreads in healthcare facilities. CDC recommends UWRC when a case is found in a unit. Currently, no recommendation exists for C. auris SOAC. We investigated if UWRC can be avoided, and clinical cases be prevented by SOAC in high-risk patients being admitted to an ICU.C. auris colonization  were screened for skin colonization with fungal axillary and groin swab cultures. These patients were placed on contact precautions pending test results. If C. auris was recovered, the patient would be upgraded to “Contact plus” precautions. If cultures were negative, precautions were downgraded to standard. No UWRC would be required if patients were identified and isolated upfront. We tracked the number of SOAC and clinical cases and compared them to the number of UWRC and clinical cases in the pre-study period.We conducted a pilot QI study in which high-risk patients for C. auris UWRCs were performed per month in reaction to 18 clinical cases, with 8 positive surveillance cultures over those 3 months (0.98% positive rate). In April 2023, our pilot study month, a total of 13 admission screening cultures were collected, of which none were positive. No UWRC were performed, and no clinical cases were detected.Between January 2023 and March 2023, an average of 273 Although limited by the pre- and post-nature, the abbreviated time, and the sample size of this pilot QI study, we found that risk based SOAC is a strategy that warrants further study as an alternative to UWRC, which are costly and labor intensive.Luis Ostrosky-Zeichner, MD, FACP, FIDSA, FSHEA, FECMM, CMQ, Astellas: Grant/Research Support|Cidara: Advisor/Consultant|Cidara: Advisor/Consultant|F2G: Advisor/Consultant|Gilead: Advisor/Consultant|Gilead: Grant/Research Support|GSK: Advisor/Consultant|Melinta: Advisor/Consultant|NIH: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support|Pfizer: Honoraria|Pulmocide: Grant/Research Support|Scynexis: Grant/Research Support|T2 Biosystems: Grant/Research Support|Viracor: Advisor/Consultant


M = 11.27 years, SD = 0.51). The participants completed the measures of materialism and demographic information at the initial time point, completed the measure of empathy about one year later, and completed the measures of prosocial and aggressive behaviors after about another year. The hypotheses were tested using a structural model using maximum likelihood estimation. The mediating effects were estimated by taking 1000 bias-corrected bootstraps. The results revealed that materialism was associated with aggressive behavior directly and positively, but had no significant correlation with prosocial behavior. Materialism had an indirect and negative correlation with prosocial behavior via empathy, while no indirect effect of materialism on aggressive behavior was found. The findings add to our knowledge of the dehumanizing nature of materialism by revealing its effect on adolescent behavioral development, as well as the underlying mechanism.Materialism plays a critical role in adolescent behavioral development, yet whether it affects prosocial and aggressive behaviors and the internal mechanism remains unknown. Therefore, this longitudinal research examined the relationships between adolescent materialism and prosocial and aggressive behaviors, and tested the mediating effect of empathy. In 2015, we recruited 543 adolescents from four junior high schools in Beijing, China (284 girls, 259 boys;  Materialism refers to a suite of goals and values that focus upon wealth, possessions, image, and status . It is aWith respect to the causes, adolescent materialism is mainly shaped via two pathways: via the experiences that elicit insecurity feelings and via exposure to the social models that encourage materialistic goals/values . With reBoth theoretical and empirical evidence suggests that values guide individual behavior ,2. As a According to what we have learned, there are two empirical studies that have focused on the relation between materialism and prosocial behavior. One study, based on adult samples, revealed that materialism altered the impact of accounting for time on prosocial behavior; that is, accounting for time decreased the time and money spent on others for participants holding moderate levels of materialism, but not for the participants with low or high levels of materialism . The othMore and more studies have focused on the impact of materialism in adolescent psychological and behavioral development; however, there is an important knowledge gap regarding the internal mechanism. Because materialism can promote a culture of dehumanization where people lack empathy for others , and empTheoretically, the dehumanizing perspective of materialism claims that materialists value material possessions over human connections and relationships, leading to a tendency to view other people as objects rather than individuals with their own thoughts, feelings, and experiences . This deEmpirically, research has found that adolescent materialism is detrimental to empathy, and empathy is predictive of prosocial and aggressive behaviors. For instance, an investigation of Hong Kong adolescents revealed a negative relationship between materialism and empathy . A longiThis research investigates the relationships between adolescents’ materialism and prosocial and aggressive behaviors, and tests the mediating effect of empathy. Based on the theoretical claim that values guide individual behavior and the dehumanizing perspective of materialism, as well as the empirical literature regarding the detrimental impact of materialism on adolescent behavioral development ,8,9, we Mage in 2015 = 11.27 years, SDage in 2015 = 0.51). About one year later, 449 of them participated at Time 2 in 2016. Ninety-four participants were unable to attend due to commitments, leading to a 17.31% attrition rate. After about another year, 417 adolescents took part at Time 3 in 2017. Because 8 of the 417 participants missed the survey at Time 2, there were 409 participants who participated in all three waves of the survey.The participants were recruited from four junior high schools in Fangshan District, Beijing, China. The first-year students in these junior high schools were sixth-graders, due to the five–four educational system . In total, 543 first-year students were recruited at Time 1 in 2015, including 284 girls and 259 boys  in appreciation of their participation. To ensure the accurate translation of the scales , which were originally in English, two graduates of English were hired to translate and back-translate them .Regarding the above survey, the omnibus (or multi-thematic) panel design was used, in which the same participants were measured on more than one occasion, but the variables measured varied from one time point to another . The varMaterialism was measured at Time 1 via six items adapted from the Youth Materialism Scale . The oriThe empathy of adolescents at Time 2 was assessed by a seven-item measure . Each itWe measured adolescent prosocial behavior using a revised version of the kindness and generosity subscale within the Values in Action Inventory of Strengths  at Time At Time 3, we measured aggressive behavior using the five items from Weinberger and Schwartz . AdolescFirst of all, the missing data and attrition analyses were performed to examine whether there were any differences between the 409 participants who stayed in the study and the 134 participants who dropped out at Time 2 and/or 3. Secondly, we used SPSS (version 26) to perform descriptive statistics and correlated analysis for the key variables. Thirdly, confirmatory factor analysis was performed for each latent construct using Mplus (version 8.3). In the fourth step, the research hypotheses were tested using a structural model with maximum likelihood estimation. Finally, we estimated the mediating effects by taking 1000 bias-corrected bootstraps. It should be noted that full information maximum likelihood (FIML), which is a missing data estimation and imputation approach for structural equation modeling, was used in the present study. Therefore, the analytic sample included 543 participants.n = 543), 22.10% of fathers and 25.60% of mothers had a junior high school diploma or lower, 33.15% of fathers and 31.31% of mothers possessed a high school diploma or equivalent educational level, 16.21% of fathers and 20.07% of mothers had a university degree, 17.50% of fathers and 14.73% of mothers had a bachelor’s degree, 3.31% of fathers and 2.21% of mothers had a master’s degree or higher, and 7.73% of fathers’ and 6.08% of mothers’ data were missing. Regarding subjective family economic status, 0.55% perceived their family as extremely poor, 4.97% perceived their family as poor, 70.17% perceived their family as average, 17.86% perceived their family as rich, 0.37% perceived their family as extremely rich, and 6.08% of the data were missing.In the analytic sample (n = 543), the missing values of the variables were from 0% to 23.76%, resulting in a total of 14.30% missing data. Little’s Missing Completely at Random (MCAR) Test was performed, and the result indicated our data were missing completely at random, χ2 (864) = 819.45, p = 0.859. Subsequently, t-tests and a Chi-square test were executed, showing that those 409 maintained participants were different from the 134 participants who dropped out at Time 2 and/or 3. The results indicated that participants with older age (p = 0.023), whose parents had lower levels of education , or with lower subjective family economic status (p = 0.001) were more prone to failure in providing responses at Time 2 and/or 3. No significant differences were found between these two groups regarding gender (p = 0.311) and materialism (p = 0.381). In summary, the sample became younger and became more biased toward better-educated and higher-economic-status families, but did not experience attrition regarding gender and materialism.For the study sample (2 (3) = 8.37, p = 0.039, CFI = 0.995, TLI = 0.975, RMSEA = 0.057, SRMR = 0.014. The factor loadings varied from 0.56 to 0.76. For empathy, the items formed a latent variable . The confirmatory factor analysis with modifications showed a good model fit: χ2 (9) = 19.18, p = 0.024, CFI = 0.985, TLI = 0.966, RMSEA = 0.050, SRMR = 0.028, and the factor loadings ranged from 0.41 to 0.74. For prosocial behavior, Cronbach’s alpha was 0.92 in the present study. We created a latent variable for it. The confirmatory factor analysis with modifications indicated good model fit: χ2 (10) = 14.60, p = 0.147, CFI = 0.998, TLI = 0.995, RMSEA = 0.033, SRMR = 0.016. The factor loadings varied from 0.69 to 0.85. For aggressive behavior, we created a latent variable for it . The model fit of confirmatory factor analysis with modifications was good: χ2 (3) = 6.16, p = 0.104, CFI = 0.997, TLI = 0.989, RMSEA = 0.050, SRMR = 0.016, with factor loadings ranging from 0.41 to 0.89.For materialism, Cronbach’s alpha was 0.80 in the present study. A latent variable was created for it. The model fit of confirmatory factor analysis with modifications was acceptable: χf2 = 0.15) suggested that at least 138 participants were needed to obtain 95% power with an α of 0.05 . Hence, the present sample size was adequate.In this structural model, we included materialism at Time 1 as the predicting variable, empathy at Time 2 as the mediator, prosocial and aggressive behaviors at Time 3 as the outcome variables, and controlled for gender, age, and subjective family economic status at Time 1. The normality of the observed variables was tested via skewness and kurtosis. The results showed that the skew values were between −1.196 and 2.055, and the kurtosis values were between −1.992 and 5.129. It has been argued that data are considered to be normal if the skewness is between −2 and +2 and the kurtosis is between −7 and +7 ,36. Thus2 (321) = 546.77, p < 0.001, CFI = 0.951, TLI = 0.943, RMSEA = 0.037, SRMR = 0.051. As indicated in p = 0.941, 95% CI = ), but was significant for aggressive behavior . Hypothesis 1 was not supported, whereas Hypothesis 2 was verified. Moreover, participants’ materialism had a negative correlation with empathy , which then positively associated with prosocial behavior  and negatively associated with aggressive behavior . There was a significant negative correlation between prosocial behavior and aggressive behavior . Additionally, the indirect effect of materialism on prosocial behavior via empathy was significant . Hypothesis 3 was verified. However, the indirect path from materialism to aggressive behavior via empathy was not significant . Hypothesis 4 was not supported. Regarding the control variables, girls showed less aggressive behavior than boys did . In terms of age, it had a positive correlation with aggressive behavior . Subjective family economic status had a positive correlation with prosocial behavior . No other significant effects of the control variables were found.The final model fit the data well: χAccording to the results, the direct effect of adolescent materialism was not significant for prosocial behavior, but was significant for aggressive behavior. Prosocial behavior and aggressive behavior were negatively correlated with each other, which is consistent with previous research ,38. The Our study did not find a direct effect of adolescent materialism on prosocial behavior. This may be due to the double-edged nature of the direct path. On the one hand, implementing prosocial behaviors brings benefits to materialistic adolescents, such as higher status among peers  and bettAs hypothesized, the indirect effect of materialism on prosocial behavior via empathy was significant. This is consistent with previous research revealing that adolescent materialism was negatively related to empathy , and thaHowever, the indirect path from adolescent materialism to aggressive behavior via empathy was not significant. Though the path from materialism to empathy was significant, as discussed earlier, the path from empathy to aggressive behavior was not significant. This is inconsistent with previous research suggesting a negative relationship between empathy and aggression in adolescents . As a deThere are some deficiencies in this study. First of all, though the study variables were assessed over a three-year period, it was an observational study and initial levels of the mediator and outcome variables were not measured and controlled for due to the omnibus (or multi-thematic) panel design of the survey. Thus, caution is needed when making causal inferences about the results. It would be beneficial to include both of the above in future research. Second, our study focused on a Chinese sample. Chinese culture emphasizes expressive suppression, which may discourage adolescents from disclosing materialistic values, hence leading to an underestimation of the relationships between the variables. Thus, the findings may be tied to this specific culture and cannot be generalized to others. It is desirable to replicate our research in different cultures. Third, convenience sampling was used and the size was relatively small, which might weaken the robustness of the results. A more rigorous sampling strategy and larger sample size would be desirable in future work. Fourth, the attrition in our sample regarding age, parental educational level, and subjective family economic status might confound the studied effects, though no attrition was found regarding gender and materialism. Therefore, more complete longitudinal samples would be fruitful to study the effects. Fifth, though empathy was found to have a mediating role regarding the relationship between adolescent materialism and prosocial behavior, there might be other potential mediators, such as self-regulation and self-esteem. Therefore, it is necessary to identify these possible underlying mechanisms in future studies.This longitudinal study investigated the relationships between materialism and prosocial and aggressive behaviors among adolescents. In addition, we tested the mediating effect of empathy regarding the above relationships. With three waves of data collected over three years in China, it was found that materialism was directly and positively related to aggressive behavior, but it had no direct correlation with prosocial behavior. Moreover, materialism had an indirect and negative correlation with prosocial behavior via empathy, while no indirect effect of materialism on aggressive behavior was found. Overall, the findings add to our knowledge of the dehumanizing nature of materialism by revealing its effect on adolescent behavioral development, as well as the underlying mechanism.The present study makes certain contributions. At the theoretical level, this study has deepened our understanding of the dehumanizing perspective of materialism and that values guide individual behavior. At the empirical level, it helps to better understand the relationship between adolescent materialism and behavioral development via focusing on both prosocial and aggressive behaviors, as well as the underlying mechanism in terms of empathy. At the practical level, given the effects of materialism on adolescent prosocial and aggressive behaviors, establishing and maintaining a healthy school climate that values interpersonal connections and relationships over material possessions could be an effective strategy for promoting prosocial behavior and reducing aggressive behavior among adolescents. In addition, educational programs and intervention projects that optimize empathy may boost the positive development of materialistic adolescents.


The 11,805 Enterobacterales from the USA were tested for susceptibility (%S) using CLSI broth microdilution with cation-adjusted Mueller-Hinton broth (CAMHB) or iron-depleted CAMHB for CFDC. Comparator agents included β-lactam/β-lactamase inhibitor (BL/BLI) combinations ceftazidime-avibactam (CZA), ceftolozane-tazobactam (C/T), imipenem-relebactam (I-R) meropenem-vaborbactam (MVB), piperacillin-tazobactam (P/T) as well as meropenem (MEM), cefepime (FEP) and ceftazidime (CAZ). Susceptibility was interpreted according to 2022 CLSI & FDA breakpoints. Carbapenem resistant Enterobacterales (CRE) was defined as resistant to imipenem (IPM) and MEM. Multidrug-resistant (MDR) Enterobacterales was defined as nonsusceptible to at least 1 drug from ≥ 3 classes and extensively drug resistant (XDR) as susceptible to ≤ 2 classes per 2022 CLSI criteria.The most common infection type from which isolates were collected was urinary tract infection , followed by bloodstream infection , pneumonia , intra-abdominal infections , and skin-soft tissue infections . Among CRE and MDR isolates, CFDC was the most active agent ( > 98%S) for isolates from BSI, PNA, and UTI. Among XDR isolates from BSI and PNA, %S to CFDC ( > 97%) was highest amongst all agents tested. Of the Bl/BLIs, C/T and P/T demonstrated the lowest %S against CRE and MDR isolates from BSI, PNA, UTI and among XDR isolates from BSI and PNA.in vitro activity against Enterobacterales regardless of infection type. Susceptibility for comparator agents was generally lower against isolates with CRE, MDR, and XDR phenotypes. CFDC represents a potential early treatment option for infections caused by Enterobacterales with presumed or defined CRE, MDR, XDR phenotypes, regardless of infection type.CFDC demonstrated high Jason J. Bryowsky, PharmD, MS, Shionogi Inc.: Employee Boudewijn L. DeJonge, PhD, Shionogi Inc.: Employee Sean T. Nguyen, PharmD, Shionogi: Employee|Shionogi, Inc: Employee Joshua Maher, PhD, AbbVie: Grant/Research Support|Affinity Biosensors: Grant/Research Support|AimMax Therapeutics, Inc: Grant/Research Support|Alterity Therapeutics: Grant/Research Support|Amicrobe, Inc: Grant/Research Support|Arietis Pharma: Grant/Research Support|Armata Pharmaceuticals, Inc: Grant/Research Support|Astrellas Pharma, Inc.: Grant/Research Support|Basilea Pharmaceutica AG: Grant/Research Support|Becton Dickinson And Company: Grant/Research Support|bioMerieux, Inc: Grant/Research Support|Boost Biomes: Grant/Research Support|Diamond V: Grant/Research Support|Fedora Pharmaceuticals, Inc: Grant/Research Support|Iterum Therapeutics plc: Grant/Research Support|Johnson & Johnson: Grant/Research Support|Kaleido Biosciences, Inc.: Grant/Research Support|Meiji Seika Pharma Co. Ltd.: Grant/Research Support|National Institutes of Health: Grant/Research Support|Pfizer Inc.: Grant/Research Support|Roche Holding AG: Grant/Research Support|Shionogi Inc.: Grant/Research Support|Summmit Therapeutics, Inc.: Grant/Research Support|Zoetis Inc: Grant/Research Support Rodrigo E. Mendes, PhD, AbbVie: Grant/Research Support|Basilea: Grant/Research Support|Cipla: Grant/Research Support|Entasis: Grant/Research Support|GSK: Grant/Research Support|Paratek: Grant/Research Support|Pfizer: Grant/Research Support|Shionogi: Grant/Research Support Miki Takemura, n/a, Shionogi & Co., Ltd.: Stocks/Bonds Yoshinori Yamano, PhD, Shionogi HQ: Employee


Ceftobiprole medocaril is currently being developed for the treatment of patients with SAB, including infective endocarditis. PK-PD target attainment analyses were performed in order to provide support for ceftobiprole dosing regimens for the treatment of patients with SAB.Ceftobiprole medocaril is an intravenously (IV) administered cephalosporin that is rapidly converted to the active moiety ceftobiprole in vitro surveillance data for S. aureus, percent probabilities of PK-PD target attainment were evaluated for ceftobiprole dosing regimens among simulated patients with SAB. Simulated patients by creatinine clearance group (CLcr) and resembling the clinical trial population of the ERADICATE Phase 3 study  were generated using replication of these clinical trial data. Dosing regimens by CLcr group that matched drug exposures to ceftobiprole 500 mg IV every 6 hours on Days 1 to 8 and every 8 hours on Day 9 and onwards among simulated patients with normal renal function were identified and then assessed among simulated patients. Randomly assigned ceftobiprole free-drug plasma %T > MIC targets associated with net bacterial stasis and a 1-log10 CFU reduction from baseline for S. aureus based on data from a neutropenic murine-thigh infection model were assessed.Using a previously developed population PK model for ceftobiprole, %T > MIC targets for efficacy, and Table 1. Table 2 shows the percent probabilities of PK-PD target attainment by MIC value and overall on Days 1 and 10. The highest MIC values at which percent probabilities of PK-PD target attainment were ≥ 90% based on free-drug plasma %T > MIC targets associated with net bacterial stasis and a 1-log10 CFU reduction from baseline for S. aureus were ≥ 4 µg/mL  among simulated patient groups. Overall percent probabilities of PK-PD target attainment were > 99.9%.Selected ceftobiprole dosing regimens for patients with SAB by CLcr group are shown in Results of PK-PD target attainment analyses provided support for ceftobiprole dosing regimens for patients with SAB with 500 mg IV every 6 hours on Days 1 to 8 and every 8 hours from Day 9. Dosing regimens were adjusted for renal function.Sujata M. Bhavnani, PharmD; MS; FIDSA, Adagio Therapeutics, Inc.: Grant/Research Support|Albany Medical Center: Grant/Research Support|Amplyx Pharmaceuticals, Inc.: Grant/Research Support|AN2 Therapeutics: Grant/Research Support|Antabio SAS: Grant/Research Support|Arcutis Biotherapeutics, Inc.: Grant/Research Support|B. Braun Medical Inc.: Grant/Research Support|Basilea Pharmaceutica: Grant/Research Support|BioFire Diagnostics LLC: Grant/Research Support|Boston Pharmaceuticals: Grant/Research Support|Cidara Therapeutics Inc.: Grant/Research Support|Cipla USA: Grant/Research Support|Crestone Inc.: Grant/Research Support|CXC: Grant/Research Support|Debiopharm International SA: Grant/Research Support|Entasis Therapeutics: Grant/Research Support|Genentech: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Hoffmann-La Roche: Grant/Research Support|ICPD: Ownership Interest|Inotrem: Grant/Research Support|Insmed Inc.: Grant/Research Support|Iterum Therapeutics Limited: Grant/Research Support|Kaizen Bioscience, Co.: Grant/Research Support|KBP Biosciences USA: Grant/Research Support|Matinas Biopharma: Grant/Research Support|Meiji Seika Pharma Co., Ltd.: Grant/Research Support|Melinta Therapeutics: Grant/Research Support|Menarini Ricerche S.p.A.: Grant/Research Support|Mutabilis: Grant/Research Support|Nabriva Therapeutics AG: Grant/Research Support|Paratek Pharmaceuticals, Inc.: Grant/Research Support|Qpex Biopharma: Grant/Research Support|Sfunga Therapeutics: Grant/Research Support|Spero Therapeutics: Grant/Research Support|Suzhou Sinovent Pharmaceuticals Co.: Grant/Research Support|Theravance: Grant/Research Support|tranScrip Partners: Grant/Research Support|University of Wisconsin: Grant/Research Support|Utility Therapeutics: Grant/Research Support|ValanBio Therapeutics Inc.: Grant/Research Support|VenatoRx: Grant/Research Support Jeffrey P. Hammel, MS, Adagio Therapeutics, Inc.: Grant/Research Support|Albany Medical Center: Grant/Research Support|Amplyx Pharmaceuticals, Inc.: Grant/Research Support|AN2 Therapeutics: Grant/Research Support|Antabio SAS: Grant/Research Support|Arcutis Biotherapeutics, Inc.: Grant/Research Support|B. Braun Medical Inc.: Grant/Research Support|Basilea Pharmaceutica: Grant/Research Support|BioFire Diagnostics LLC: Grant/Research Support|Boston Pharmaceuticals: Grant/Research Support|Cidara Therapeutics Inc.: Grant/Research Support|Cipla USA: Grant/Research Support|Crestone Inc.: Grant/Research Support|CXC: Grant/Research Support|Debiopharm International SA: Grant/Research Support|Entasis Therapeutics: Grant/Research Support|Genentech: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Hoffmann-La Roche: Grant/Research Support|ICPD: Employee|Inotrem: Grant/Research Support|Insmed Inc.: Grant/Research Support|Iterum Therapeutics Limited: Grant/Research Support|Kaizen Bioscience, Co.: Grant/Research Support|KBP Biosciences USA: Grant/Research Support|Matinas Biopharma: Grant/Research Support|Meiji Seika Pharma Co., Ltd.: Grant/Research Support|Melinta Therapeutics: Grant/Research Support|Menarini Ricerche S.p.A.: Grant/Research Support|Mutabilis: Grant/Research Support|Nabriva Therapeutics AG: Grant/Research Support|Paratek Pharmaceuticals, Inc.: Grant/Research Support|Qpex Biopharma: Grant/Research Support|Sfunga Therapeutics: Grant/Research Support|Spero Therapeutics: Grant/Research Support|Suzhou Sinovent Pharmaceuticals Co.: Grant/Research Support|Theravance: Grant/Research Support|tranScrip Partners: Grant/Research Support|University of Wisconsin: Grant/Research Support|Utility Therapeutics: Grant/Research Support|ValanBio Therapeutics Inc.: Grant/Research Support|VenatoRx: Grant/Research Support Anthony J. Rinaldo, B.S., Adagio Therapeutics, Inc.: Grant/Research Support|Albany Medical Center: Grant/Research Support|Amplyx Pharmaceuticals, Inc.: Grant/Research Support|AN2 Therapeutics: Grant/Research Support|Antabio SAS: Grant/Research Support|Arcutis Biotherapeutics, Inc.: Grant/Research Support|B. Braun Medical Inc.: Grant/Research Support|Basilea Pharmaceutica: Grant/Research Support|BioFire Diagnostics LLC: Grant/Research Support|Boston Pharmaceuticals: Grant/Research Support|Cidara Therapeutics Inc.: Grant/Research Support|Cipla USA: Grant/Research Support|Crestone Inc.: Grant/Research Support|CXC: Grant/Research Support|Debiopharm International SA: Grant/Research Support|Entasis Therapeutics: Grant/Research Support|Genentech: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Hoffmann-La Roche: Grant/Research Support|ICPD: Employee|Inotrem: Grant/Research Support|Insmed Inc.: Grant/Research Support|Iterum Therapeutics Limited: Grant/Research Support|Kaizen Bioscience, Co.: Grant/Research Support|KBP Biosciences USA: Grant/Research Support|Matinas Biopharma: Grant/Research Support|Meiji Seika Pharma Co., Ltd.: Grant/Research Support|Melinta Therapeutics: Grant/Research Support|Menarini Ricerche S.p.A.: Grant/Research Support|Mutabilis: Grant/Research Support|Nabriva Therapeutics AG: Grant/Research Support|Paratek Pharmaceuticals, Inc.: Grant/Research Support|Qpex Biopharma: Grant/Research Support|Sfunga Therapeutics: Grant/Research Support|Spero Therapeutics: Grant/Research Support|Suzhou Sinovent Pharmaceuticals Co.: Grant/Research Support|Theravance: Grant/Research Support|tranScrip Partners: Grant/Research Support|University of Wisconsin: Grant/Research Support|Utility Therapeutics: Grant/Research Support|ValanBio Therapeutics Inc.: Grant/Research Support|VenatoRx: Grant/Research Support Jennifer Smart, PhD, Basilea Pharmaceutica International Ltd, Allschwil, Switzerland: Stocks/Bonds Karine Litherland, Ph.D., Basilea Pharmaceutica International Ltd, Allschwil, Switzerland: Full time employee|Basilea Pharmaceutica International Ltd, Allschwil, Switzerland: Stocks/Bonds Leonard R. Duncan, PhD, AbbVie: Grant/Research Support|Basilea: Grant/Research Support|CorMedix: Grant/Research Support|Melinta: Grant/Research Support|Pfizer: Grant/Research Support Mark E. Jones, PhD, Astellas Pharma Global Development, Inc: Support for the present publication|Basilea Pharmaceutica International Ltd: Employee of Basilea Pharmaceutica International Ltd|Basilea Pharmaceutica International Ltd: Stocks/Bonds Marc Engelhardt, MD, Astellas Pharma Global Development, Inc.: Support for the present publication|Basilea Pharmaceutica International Ltd: Employee of Basilea Pharmaceutica International Ltd|Basilea Pharmaceutica International Ltd: Stocks/Bonds Paul G. Ambrose, PharmD; MS; FIDSA, Adagio Therapeutics, Inc.: Grant/Research Support|Albany Medical Center: Grant/Research Support|Amplyx Pharmaceuticals, Inc.: Grant/Research Support|AN2 Therapeutics: Grant/Research Support|Antabio SAS: Grant/Research Support|Arcutis Biotherapeutics, Inc.: Grant/Research Support|B. Braun Medical Inc.: Grant/Research Support|Basilea Pharmaceutica: Grant/Research Support|BioFire Diagnostics LLC: Grant/Research Support|Boston Pharmaceuticals: Grant/Research Support|Cidara Therapeutics Inc.: Grant/Research Support|Cipla USA: Grant/Research Support|Crestone Inc.: Grant/Research Support|CXC: Grant/Research Support|Debiopharm International SA: Grant/Research Support|Entasis Therapeutics: Grant/Research Support|Genentech: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Hoffmann-La Roche: Grant/Research Support|ICPD: Ownership Interest|Inotrem: Grant/Research Support|Insmed Inc.: Grant/Research Support|Iterum Therapeutics Limited: Grant/Research Support|Kaizen Bioscience, Co.: Grant/Research Support|KBP Biosciences USA: Grant/Research Support|Matinas Biopharma: Grant/Research Support|Meiji Seika Pharma Co., Ltd.: Grant/Research Support|Melinta Therapeutics: Grant/Research Support|Menarini Ricerche S.p.A.: Grant/Research Support|Mutabilis: Grant/Research Support|Nabriva Therapeutics AG: Grant/Research Support|Paratek Pharmaceuticals, Inc.: Grant/Research Support|Qpex Biopharma: Grant/Research Support|Sfunga Therapeutics: Grant/Research Support|Spero Therapeutics: Grant/Research Support|Suzhou Sinovent Pharmaceuticals Co.: Grant/Research Support|Theravance: Grant/Research Support|tranScrip Partners: Grant/Research Support|University of Wisconsin: Grant/Research Support|Utility Therapeutics: Grant/Research Support|ValanBio Therapeutics Inc.: Grant/Research Support|VenatoRx: Grant/Research Support Christopher M. Rubino, PharmD, Adagio Therapeutics, Inc.: Grant/Research Support|Albany Medical Center: Grant/Research Support|Amplyx Pharmaceuticals, Inc.: Grant/Research Support|AN2 Therapeutics: Grant/Research Support|Antabio SAS: Grant/Research Support|Arcutis Biotherapeutics, Inc.: Grant/Research Support|B. Braun Medical Inc.: Grant/Research Support|Basilea Pharmaceutica: Grant/Research Support|BioFire Diagnostics LLC: Grant/Research Support|Boston Pharmaceuticals: Grant/Research Support|Cidara Therapeutics Inc.: Grant/Research Support|Cipla USA: Grant/Research Support|Crestone Inc.: Grant/Research Support|CXC: Grant/Research Support|Debiopharm International SA: Grant/Research Support|Entasis Therapeutics: Grant/Research Support|Genentech: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Hoffmann-La Roche: Grant/Research Support|ICPD: Ownership Interest|Inotrem: Grant/Research Support|Insmed Inc.: Grant/Research Support|Iterum Therapeutics Limited: Grant/Research Support|Kaizen Bioscience, Co.: Grant/Research Support|KBP Biosciences USA: Grant/Research Support|Matinas Biopharma: Grant/Research Support|Meiji Seika Pharma Co., Ltd.: Grant/Research Support|Melinta Therapeutics: Grant/Research Support|Menarini Ricerche S.p.A.: Grant/Research Support|Mutabilis: Grant/Research Support|Nabriva Therapeutics AG: Grant/Research Support|Paratek Pharmaceuticals, Inc.: Grant/Research Support|Qpex Biopharma: Grant/Research Support|Sfunga Therapeutics: Grant/Research Support|Spero Therapeutics: Grant/Research Support|Suzhou Sinovent Pharmaceuticals Co.: Grant/Research Support|Theravance: Grant/Research Support|tranScrip Partners: Grant/Research Support|University of Wisconsin: Grant/Research Support|Utility Therapeutics: Grant/Research Support|ValanBio Therapeutics Inc.: Grant/Research Support|VenatoRx: Grant/Research Support