Quantifying Smooth Muscles Regional Organization in the Rat Bladder Using Immunohistochemistry, Multiphoton Microscopy and Machine Learning.

The smooth muscle bundles (SMBs) in the bladder act as contractile elements which enable the bladder to void effectively. In contrast to skeletal muscles, these bundles are not highly aligned, rather they are oriented more heterogeneously throughout the bladder wall. In this work, for the first time, this regional orientation of the SMBs is quantified across the whole bladder, without the need for optical clearing or cryosectioning. Immunohistochemistry staining was utilized to visualize smooth muscle cell actin in multiphoton microscopy (MPM) images of bladder smooth muscle bundles (SMBs). Feature vectors for each pixel were generated using a range of filters, including Gaussian blur, Gaussian gradient magnitude, Laplacian of Gaussian, Hessian eigenvalues, structure tensor eigenvalues, Gabor, and Sobel gradients. A Random Forest classifier was subsequently trained to automate the segmentation of SMBs in the MPM images. Finally, the orientation of SMBs in each bladder region was quantified using the CT-FIRE package. This information is essential for biomechanical models of the bladder that include contractile elements.

Pathophysiology of Overactive Bladder and Pharmacologic Treatments Including ß3-Adrenoceptor Agonists -Basic Research Perspectives.

Overactive bladder (OAB) is a symptom-based syndrome defined by urinary urgency, frequency, and nocturia with or without urge incontinence. The causative pathology is diverse; including bladder outlet obstruction (BOO), bladder ischemia, aging, metabolic syndrome, psychological stress, affective disorder, urinary microbiome, localized and systemic inflammatory responses, etc. Several hypotheses have been suggested as mechanisms of OAB generation; among them, neurogenic, myogenic, and urothelial mechanisms are well-known hypotheses. Also, a series of local signals called autonomous myogenic contraction, micromotion, or afferent noises, which can occur during bladder filling, may be induced by the leak of acetylcholine (ACh) or urothelial release of adenosine triphosphate (ATP). They can be transmitted to the central nervous system through afferent fibers to trigger coordinated urgency-related detrusor contractions. Antimuscarinics, commonly known to induce smooth muscle relaxation by competitive blockage of muscarinic receptors in the parasympathetic postganglionic nerve, have a minimal effect on detrusor contraction within therapeutic doses. In fact, they have a predominant role in preventing signals in the afferent nerve transmission process. ß3-adrenergic receptor (AR) agonists inhibit afferent signals by predominant inhibition of mechanosensitive Aδ-fibers in the normal bladder. However, in pathologic conditions such as spinal cord injury, it seems to inhibit capsaicin-sensitive C-fibers. Particularly, mirabegron, a ß3-agonist, prevents ACh release in the BOO-induced detrusor overactivity model by parasympathetic prejunctional mechanisms. A recent study also revealed that vibegron may have 2 mechanisms of action: inhibition of ACh from cholinergic efferent nerves in the detrusor and afferent inhibition via urothelial ß3-AR.

Comapping Cellular Content and Extracellular Matrix with Hemodynamics in Intact Arterial Tissues Using Scanning Immunofluorescent Multiphoton Microscopy.

Deviation of blood flow from an optimal range is known to be associated with the initiation and progression of vascular pathologies. Important open questions remain about how the abnormal flow drives specific wall changes in pathologies such as cerebral aneurysms where the flow is highly heterogeneous and complex. This knowledge gap precludes the clinical use of readily available flow data to predict outcomes and improve treatment of these diseases. As both flow and the pathological wall changes are spatially heterogeneous, a crucial requirement for progress in this area is a methodology for acquiring and comapping local vascular wall biology data with local hemodynamic data. Here, we developed an imaging pipeline to address this pressing need. A protocol that employs scanning multiphoton microscopy was developed to obtain three-dimensional (3D) datasets for smooth muscle actin, collagen, and elastin in intact vascular specimens. A cluster analysis was introduced to objectively categorize the smooth muscle cells (SMC) across the vascular specimen based on SMC actin density. Finally, direct quantitative comparison of local flow and wall biology in 3D intact specimens was achieved by comapping both heterogeneous SMC data and wall thickness to patient-specific hemodynamic results.

Phenotyping calcification in vascular tissues using artificial intelligence.

Vascular calcification is implicated as an important factor in major adverse cardiovascular events (MACE), including heart attack and stroke. A controversy remains over how to integrate the diverse forms of vascular calcification into clinical risk assessment tools. Even the commonly used calcium score for coronary arteries, which assumes risk scales positively with total calcification, has important inconsistencies. Fundamental studies are needed to determine how risk is influenced by the diverse calcification phenotypes. However, studies of these kinds are hindered by the lack of high-throughput, objective, and non-destructive tools for classifying calcification in imaging data sets. Here, we introduce a new classification system for phenotyping calcification along with a semi-automated, non-destructive pipeline that can distinguish these phenotypes in even atherosclerotic tissues. The pipeline includes a deep-learning-based framework for segmenting lipid pools in noisy µ-CT images and an unsupervised clustering framework for categorizing calcification based on size, clustering, and topology. This approach is illustrated for five vascular specimens, providing phenotyping for thousands of calcification particles across as many as 3200 images in less than seven hours. Average Dice Similarity Coefficients of 0.96 and 0.87 could be achieved for tissue and lipid pool, respectively, with training and validation needed on only 13 images despite the high heterogeneity in these tissues. By introducing an efficient and comprehensive approach to phenotyping calcification, this work enables large-scale studies to identify a more reliable indicator of the risk of cardiovascular events, a leading cause of global mortality and morbidity.

Groundwater is a hidden global keystone ecosystem.

Groundwater is a vital ecosystem of the global water cycle, hosting unique biodiversity and providing essential services to societies. Despite being the largest unfrozen freshwater resource, in a period of depletion by extraction and pollution, groundwater environments have been repeatedly overlooked in global biodiversity conservation agendas. Disregarding the importance of groundwater as an ecosystem ignores its critical role in preserving surface biomes. To foster timely global conservation of groundwater, we propose elevating the concept of keystone species into the realm of ecosystems, claiming groundwater as a keystone ecosystem that influences the integrity of many dependent ecosystems. Our global analysis shows that over half of land surface areas (52.6%) has a medium-to-high interaction with groundwater, reaching up to 74.9% when deserts and high mountains are excluded. We postulate that the intrinsic transboundary features of groundwater are critical for shifting perspectives towards more holistic approaches in aquatic ecology and beyond. Furthermore, we propose eight key themes to develop a science-policy integrated groundwater conservation agenda. Given ecosystems above and below the ground intersect at many levels, considering groundwater as an essential component of planetary health is pivotal to reduce biodiversity loss and buffer against climate change.

Co-mapping Cellular Content and Extracellular Matrix with Hemodynamics in Intact Arterial Tissues Using Scanning Immunofluorescent Multiphoton Microscopy.

Deviation of blood flow from an optimal range is known to be associated with the initiation and progression of vascular pathologies. Important open questions remain about how the abnormal flow drives specific wall changes in pathologies such as cerebral aneurysms where the flow is highly heterogeneous and complex. This knowledge gap precludes the clinical use of readily available flow data to predict outcomes and improve treatment of these diseases. As both flow and the pathological wall changes are spatially heterogeneous, a crucial requirement for progress in this area is a methodology for co-mapping local data from vascular wall biology with local hemodynamic data. In this study, we developed an imaging pipeline to address this pressing need. A protocol that employs scanning multiphoton microscopy was designed to obtain 3D data sets for smooth muscle actin, collagen and elastin in intact vascular specimens. A cluster analysis was developed to objectively categorize the smooth muscle cells (SMC) across the vascular specimen based on SMC density. In the final step in this pipeline, the location specific categorization of SMC, along with wall thickness was co-mapped with patient specific hemodynamic results, enabling direct quantitative comparison of local flow and wall biology in 3D intact specimens.

Evaluation of predictive models of aneurysm focal growth and bleb development using machine learning techniques.

BACKGROUND: The presence of blebs increases the rupture risk of intracranial aneurysms (IAs). OBJECTIVE: To evaluate whether cross-sectional bleb formation models can identify aneurysms with focalized enlargement in longitudinal series. METHODS: Hemodynamic, geometric, and anatomical variables derived from computational fluid dynamics models of 2265 IAs from a cross-sectional dataset were used to train machine learning (ML) models for bleb development. ML algorithms, including logistic regression, random forest, bagging method, support vector machine, and K-nearest neighbors, were validated using an independent cross-sectional dataset of 266 IAs. The models' ability to identify aneurysms with focalized enlargement was evaluated using a separate longitudinal dataset of 174 IAs. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), the sensitivity and specificity, positive predictive value, negative predictive value, F1 score, balanced accuracy, and misclassification error. RESULTS: The final model, with three hemodynamic and four geometrical variables, along with aneurysm location and morphology, identified strong inflow jets, non-uniform wall shear stress with high peaks, larger sizes, and elongated shapes as indicators of a higher risk of focal growth over time. The logistic regression model demonstrated the best performance on the longitudinal series, achieving an AUC of 0.9, sensitivity of 85%, specificity of 75%, balanced accuracy of 80%, and a misclassification error of 21%. CONCLUSIONS: Models trained with cross-sectional data can identify aneurysms prone to future focalized growth with good accuracy. These models could potentially be used as early indicators of future risk in clinical practice.

Structural basis for inactivation of PRC2 by G-quadruplex RNA.

Polycomb repressive complex 2 (PRC2) silences genes through trimethylation of histone H3K27. PRC2 associates with numerous precursor messenger RNAs (pre-mRNAs) and long noncoding RNAs (lncRNAs) with a binding preference for G-quadruplex RNA. In this work, we present a 3.3-Å-resolution cryo-electron microscopy structure of PRC2 bound to a G-quadruplex RNA. Notably, RNA mediates the dimerization of PRC2 by binding both protomers and inducing a protein interface composed of two copies of the catalytic subunit EZH2, thereby blocking nucleosome DNA interaction and histone H3 tail accessibility. Furthermore, an RNA-binding loop of EZH2 facilitates the handoff between RNA and DNA, another activity implicated in PRC2 regulation by RNA. We identified a gain-of-function mutation in this loop that activates PRC2 in zebrafish. Our results reveal mechanisms for RNA-mediated regulation of a chromatin-modifying enzyme.

Transcription factors interact with RNA to regulate genes.

Transcription factors (TFs) orchestrate the gene expression programs that define each cell's identity. The canonical TF accomplishes this with two domains, one that binds specific DNA sequences and the other that binds protein coactivators or corepressors. We find that at least half of TFs also bind RNA, doing so through a previously unrecognized domain with sequence and functional features analogous to the arginine-rich motif of the HIV transcriptional activator Tat. RNA binding contributes to TF function by promoting the dynamic association between DNA, RNA, and TF on chromatin. TF-RNA interactions are a conserved feature important for vertebrate development and disrupted in disease. We propose that the ability to bind DNA, RNA, and protein is a general property of many TFs and is fundamental to their gene regulatory function.

Hypoxanthine Induces Signs of Bladder Aging with Voiding dysfunction and Lower Urinary Tract Remodeling.

BACKGROUND: Lower urinary tract syndrome (LUTS) is a group of urinary tract symptoms and signs which can include urinary incontinence. Advancing age is a major risk factors for LUTS; however the underlying biochemical mechanisms of age-related LUTS remain unknown. HX (hypoxanthine) is a purine metabolite associated with generation of tissue damaging reactive oxygen species (ROS). This study tested the hypothesis that exposure of the adult bladder to HX-ROS over time damages key LUT elements, mimicking qualitatively some of the changes observed with aging. METHODS: Adult 3-month-old female Fischer 344 (F344) rats were treated with vehicle or HX (10 mg/kg/day; 3 weeks) administered in drinking water. Targeted purine metabolomics and molecular approaches were used to assess purine metabolites and biomarkers for oxidative stress and cellular damage. Biomechanical approaches assessed LUT structure and measurements of LUT function (using custom-metabolic cages and cystometry) were also employed. RESULTS: HX exposure increased biomarkers indicative of oxidative stress, pathophysiological ROS production and depletion of cellular energy with declines in NAD + levels. Moreover, HX treatment caused bladder remodeling and decreased the intercontraction interval and leak point pressure (surrogate measure to assess stress urinary incontinence). CONCLUSIONS: These studies provide evidence that in adult rats chronic exposure to HX causes changes in voiding behavior and in bladder structure resembling alterations observed with aging. These results suggest that increased levels of uro-damaging HX were associated with ROS/oxidative stress-associated cellular damage which may be central to age-associated development of LUTS, opening up potential opportunities for geroscience-guided interventions.

Computational fluid dynamics-based virtual angiograms for the detection of flow stagnation in intracranial aneurysms.

The goal of this study was to test if CFD-based virtual angiograms could be used to automatically discriminate between intracranial aneurysms (IAs) with and without flow stagnation. Time density curves (TDC) were extracted from patient digital subtraction angiography (DSA) image sequences by computing the average gray level intensity inside the aneurysm region and used to define injection profiles for each subject. Subject-specific 3D models were reconstructed from 3D rotational angiography (3DRA) and computational fluid dynamics (CFD) simulations were performed to simulate the blood flow inside IAs. Transport equations were solved numerically to simulate the dynamics of contrast injection into the parent arteries and IAs and then the contrast retention time (RET) was calculated. The importance of gravitational pooling of contrast agent within the aneurysm was evaluated by modeling contrast agent and blood as a mixture of two fluids with different densities and viscosities. Virtual angiograms can reproduce DSA sequences if the correct injection profile is used. RET can identify aneurysms with significant flow stagnation even when the injection profile is not known. Using a small sample of 14 IAs of which seven were previously classified as having flow stagnation, it was found that a threshold RET value of 0.46 s can successfully identify flow stagnation. CFD-based prediction of stagnation was in more than 90% agreement with independent visual DSA assessment of stagnation in a second sample of 34 IAs. While gravitational pooling prolonged contrast retention time it did not affect the predictive capabilities of RET. CFD-based virtual angiograms can detect flow stagnation in IAs and can be used to automatically identify aneurysms with flow stagnation even without including gravitational effects on contrast agents.

Multimodal exploration of the intracranial aneurysm wall.

PURPOSE: Intracranial aneurysms (IAs) are pathological changes of the intracranial vessel wall, although clinical image data can only show the vessel lumen. Histology can provide wall information but is typically restricted to ex vivo 2D slices where the shape of the tissue is altered. METHODS: We developed a visual exploration pipeline for a comprehensive view of an IA. We extract multimodal information (like stain classification and segmentation of histologic images) and combine them via 2D to 3D mapping and virtual inflation of deformed tissue. Histological data, including four stains, micro-CT data and segmented calcifications as well as hemodynamic information like wall shear stress (WSS), are combined with the 3D model of the resected aneurysm. RESULTS: Calcifications were mostly present in the tissue part with increased WSS. In the 3D model, an area of increased wall thickness was identified and correlated to histology, where the Oil red O (ORO) stained images showed a lipid accumulation and the alpha-smooth muscle actin (aSMA) stained images showed a slight loss of muscle cells. CONCLUSION: Our visual exploration pipeline combines multimodal information about the aneurysm wall to improve the understanding of wall changes and IA development. The user can identify regions and correlate how hemodynamic forces, e.g. WSS, are reflected by histological structures of the vessel wall, wall thickness and calcifications.

Differences Between Ruptured Aneurysms With and Without Blebs: Mechanistic Implications.

PURPOSE: Blebs are known risk factors for intracranial aneurysm (IA) rupture. We analyzed differences between IAs that ruptured with blebs and those that ruptured without developing blebs to identify distinguishing characteristics among them and suggest possible mechanistic implications. METHODS: Using image-based models, 25 hemodynamic and geometric parameters were compared between ruptured IAs with and without blebs (n = 673), stratified by location. Hemodynamic and geometric differences between bifurcation and sidewall aneurysms and for aneurysms at five locations were also analyzed. RESULTS: Ruptured aneurysms harboring blebs were exposed to higher flow conditions than aneurysms that ruptured without developing blebs, and this was consistent across locations. Bifurcation aneurysms were exposed to higher flow conditions than sidewall aneurysms. They had larger maximum wall shear stress (WSS), more concentrated WSS distribution, and larger numbers of critical points than sidewall aneurysms. Additionally, bifurcation aneurysms were larger, more elongated, and had more distorted shapes than sidewall aneurysms. Aneurysm morphology was associated with aneurysm location (p < 0.01). Flow conditions were different between aneurysm locations. CONCLUSION: Aneurysms at different locations are likely to develop into varying morphologies and thus be exposed to diverse flow conditions that may predispose them to follow distinct pathways towards rupture with or without bleb development. This could explain the diverse rupture rates and bleb presence in aneurysms at different locations.

Intermediate Levels of Predation and Nutrient Enrichment Enhance the Activity of Ibuprofen-Degrading Bacteria.

Water is the most indispensable natural resource; yet, organic pollution of freshwater sources is widespread. In recent years, there has been increasing concern over the vast array of emerging organic contaminants (EOCs) in the effluent of wastewater treatment plants (WWTPs). Several of these EOCs are degraded within the pore space of riverbeds by active microbial consortia. However, the mechanisms behind this ecosystem service are largely unknown. Here, we report how phosphate concentration and predator-prey interactions drive the capacity of bacteria to process a model EOC (ibuprofen). The presence of phosphate had a significant positive effect on the population growth rate of an ibuprofen-degrading strain. Thus, when phosphate was present, ibuprofen removal efficiency increased. Moreover, low and medium levels of predation, by a ciliated protozoan, stimulated bacterial population growth. This unimodal effect of predation was lost under high phosphate concentration, resulting in the flattening of the relationships between predator density and population growth of ibuprofen degraders. Our results suggest that moderate nutrient and predation levels promote the growth rate of bacterial degraders and, consequently, the self-purifying capability of the system. These findings enhance our understanding of the mechanisms by which riverbed communities drive the processing of EOCs.

A constrained mixture-micturition-growth (CMMG) model of the urinary bladder: Application to partial bladder outlet obstruction (BOO).

We present a constrained mixture-micturition-growth (CMMG) model for the bladder. It simulates bladder mechanics, voiding function (micturition) and tissue adaptations in response to altered biomechanical conditions. The CMMG model is calibrated with both in vivo and in vitro data from healthy male rat urinary bladders (cystometry, bioimaging of wall structure, mechanical testing) and applied to simulate the growth and remodeling (G&R) response to partial bladder outlet obstruction (BOO). The bladder wall is represented as a multi-layered, anisotropic, nonlinear constrained mixture. A short time scale micturition component of the CMMG model accounts for the active and passive mechanics of voiding. Over a second, longer time scale, G&R algorithms for the evolution of both cellular and extracellular constituents act to maintain/restore bladder (homeostatic) functionality. The CMMG model is applied to a spherical membrane model of the BOO bladder utilizing temporal data from an experimental male rodent model to parameterize and then verify the model. Consistent with the experimental studies of BOO, the model predicts: an initial loss of voiding capacity followed by hypertrophy of SMC to restore voiding function; bladder enlargement; collagen remodeling to maintain its role as a protective sheath; and increased voiding duration with lower average flow rate. This CMMG model enables a mechanistic approach for investigating the bladder's structure-function relationship and its adaption in pathological conditions. While the approach is illustrated with a conceptual spherical bladder model, it provides the basis for application of the CMMG model to anatomical geometries. Such a mechanistic approach has promise as an in silico tool for the rational development of new surgical and pharmacological treatments for bladder diseases such as BOO.

Correction: Danner et al. It More than Adds Up: Interaction of Antibiotic Mixing and Temperature. Life 2021, 11, 1435.

The Authors wish to make the following corrections to this paper [...].

Prediction of bleb formation in intracranial aneurysms using machine learning models based on aneurysm hemodynamics, geometry, location, and patient population.

BACKGROUND: Bleb presence in intracranial aneurysms (IAs) is a known indication of instability and vulnerability. OBJECTIVE: To develop and evaluate predictive models of bleb development in IAs based on hemodynamics, geometry, anatomical location, and patient population. METHODS: Cross-sectional data (one time point) of 2395 IAs were used for training bleb formation models using machine learning (random forest, support vector machine, logistic regression, k-nearest neighbor, and bagging). Aneurysm hemodynamics and geometry were characterized using image-based computational fluid dynamics. A separate dataset with 266 aneurysms was used for model evaluation. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), true positive rate (TPR), false positive rate (FPR), precision, and balanced accuracy. RESULTS: The final model retained 18 variables, including hemodynamic, geometrical, location, multiplicity, and morphology parameters, and patient population. Generally, strong and concentrated inflow jets, high speed, complex and unstable flow patterns, and concentrated, oscillatory, and heterogeneous wall shear stress patterns together with larger, more elongated, and more distorted shapes were associated with bleb formation. The best performance on the validation set was achieved by the random forest model (AUC=0.82, TPR=91%, FPR=36%, misclassification error=27%). CONCLUSIONS: Based on the premise that aneurysm characteristics prior to bleb formation resemble those derived from vascular reconstructions with their blebs virtually removed, machine learning models can identify aneurysms prone to bleb development with good accuracy. Pending further validation with longitudinal data, these models may prove valuable for assessing the propensity of IAs to progress to vulnerable states and potentially rupturing.

Predicting regression of cervical intraepithelial neoplasia grade 2 in women under 25 years.

BACKGROUND: A number of retrospective and prospective studies have documented substantial rates of regression in cervical intraepithelial neoplasia grade 2 lesions in young women. Initial observational management of cervical intraepithelial neoplasia grade 2 is increasingly accepted as appropriate for women under 25 years of age with screen-detected abnormalities and is included in a number of clinical guidelines. However, there has been a paucity of large prospective studies on observational management with strict inclusion criteria. A number of important questions remain, specifically regarding the clinical variables that are associated with the risk of progression or persistence of disease. To investigate these factors and to ensure that young women with cervical intraepithelial neoplasia grade 2 undergoing observational management were being managed in a well-monitored and an appropriately informed fashion, we conducted a large, multicenter prospective study on observational management of cervical intraepithelial neoplasia grade 2 in women under 25 years. OBJECTIVE: This study aimed to determine the regression rates and clinical, cytologic, and pathologic predictors of regression of cervical intraepithelial neoplasia grade 2 in women under 25 years undergoing observational management over 24 months. STUDY DESIGN: This study was a multicenter prospective study on observational management of cervical intraepithelial neoplasia grade 2 (ie, repeat colposcopy, cytology, and cervical biopsy every 6 months) for up to 24 months. A total of 615 consenting women under 25 years with newly-diagnosed, biopsy-proven cervical intraepithelial neoplasia grade 2 were recruited (from 2010 to 2016) through 16 hospital-based colposcopy units in New Zealand and Australia. RESULTS: At completion, 326 women had confirmed regression, 156 had persistent high-grade cervical intraepithelial neoplasia grade 2 or 3 or adenocarcinoma in situ, and 24 had unconfirmed regression (ie, first regression at the 24-month follow-up). A total of 109 women did not complete the protocol (41 because of delayed follow-up, 41 lost to follow-up, 22 elected treatment, 4 refused a biopsy, and 1 died of an unrelated cause). Confirmed regression was observed in 53% (326 of 615) of all women enrolled in the study and, when missing data were imputed, it was estimated that 64% of women (95% confidence interval, 60%-68%) would have experienced regression. Similarly, lesions regressed in 64% (326 of 506) of women who completed the observational protocol. Based on a multivariable analysis, detection of human papillomavirus 16 in a liquid-based cytology sample at the time of initial colposcopy decreased the chance of regression by 31% (risk ratio, 0.69; 95% confidence interval, 0.56-0.86; P<.001). In addition, at initial colposcopy, low-grade or normal colposcopic impression, later year of diagnosis, low-grade or normal cytology, and being a nonsmoker were all independently associated with an increased chance of regression. CONCLUSION: More than half of women under 25 years with cervical intraepithelial neoplasia grade 2 will regress to cervical intraepithelial neoplasia grade 1 or normal within 24 months without destructive treatment. The absence of human papillomavirus 16 is the most important predictor of regression.

It More than Adds Up: Interaction of Antibiotic Mixing and Temperature.

Use of antibiotics for the treatment and prevention of bacterial infections in humans, agri- and aquaculture as well as livestock rearing leads to antibiotic pollution of fresh water and these antibiotics have an impact on free-living bacteria. While we know which antibiotics are most common in natural environments such as rivers and streams, there is considerable uncertainty regarding antibiotics' interactions with one another and the effect of abiotic factors such as temperature. Here, we used an experimental approach to explore the effects of antibiotic identity, concentration, mixing and water temperature on the growth of Pseudomonas fluorescens, a common, ubiquitous bacterium. We exposed P. fluorescens to the four antibiotics most commonly found in surface waters (ciprofloxacin, ofloxacin, sulfamethoxazole and sulfapyridine) and investigated antibiotic interactions for single and mixed treatments at different, field-realistic temperatures. We observed an overall dependence of antibiotic potency on temperature, as temperature increased efficacy of ciprofloxacin and ofloxacin with their EC50 lowered by >75% with a 10 °C temperature increase. Further, we show that mixtures of ciprofloxacin and ofloxacin, despite both belonging to the fluoroquinolone class, exhibit low-temperature-dependent synergistic effects in inhibiting bacterial growth. These findings highlight the context dependency of antibiotic efficacy. They further suggest antibiotic-specific off-target effects that only affect the bacteria once they enter a certain temperature range. This has important implications as freshwater systems already contain multi-drug antibiotic cocktails and are changing temperature due to environmental warming. These factors will interact and affect aquatic food webs, and hence this creates an urgent need to adapt and improve laboratory testing conditions to closer reflect natural environments.