Novel sunlight-induced monochloramine activation system for efficient microcontaminant abatement.

As an eco-friendly and sustainable energy, solar energy has great application potential in water treatment. Herein, simulated sunlight was for the first time utilized to activate monochloramine for the degradation of environmental organic microcontaminants. Various microcontaminants could be efficiently degraded in the simulated sunlight/monochloramine system. The average innate quantum yield of monochloramine over the wavelength range of simulated sunlight was determined to be 0.068 mol/Einstein. With the determined quantum yield, a kinetic model was established. Based on the good agreement between the simulated and measured photolysis and radical contributions to the degradation of ibuprofen and carbamazepine, the major mechanism of monochloramine activation by simulated sunlight was proposed. Chlorine radical (Cl∙) and hydroxyl radical (HO∙) were major radicals responsible for microcontaminant degradation in the system. Moreover, the model facilitated a deep investigation into the effects of different reaction conditions (pH, monochloramine concentration, and water matrix components) on the degradation of ibuprofen and carbamazepine, as well as the roles of the involved radicals. The differences between simulated and measured degradation data of each microcontaminant under all conditions were less than 10 %, indicating the strong reliability of the model. The model could also make good prediction for microcontaminant degradation in the natural sunlight/monochloramine system. Furthermore, the formation of disinfection byproducts (DBPs) was evaluated at different oxidation time in simulated sunlight/monochloramine with and without post-chloramination treatment. In real waters, organic components showed more pronounced suppression on microcontaminant degradation efficiency than inorganic ions. This study provided a systematic investigation into the novel sunlight-induced monochloramine activation system for efficient microcontaminant degradation, and demonstrated the potential of the system in practical applications.

Refinement of kinetic model and understanding the role of dichloride radical (Cl2•-) in radical transformation in the UV/NH2Cl process.

The ultraviolet/monochloramine (UV/NH2Cl) process is an emerging advanced oxidation process with promising prospects in water treatment. Previous studies developed kinetic models of UV/NH2Cl for simulating radical concentrations and pollutant degradation. However, the reaction rate constants of Cl2•- with bicarbonate and carbonate (kCl2•-, HCO3- and kCl2•-, CO32-) were overestimated in literature. Consequently, when dosing 1 mM chloride and 1 mM bicarbonate, the current models of UV/NH2Cl severely under-predicted the experimental concentrations of three important radicals (i.e., hydroxyl radical (HO•), chlorine radical (Cl•), and dichloride radical (Cl2•-)) with great deviations (> 90 %). To investigate this issue, the transformation reactions among these three radicals in UV/NH2Cl were systematically studied. For the first time, it was found that in addition to Cl•, Cl2•- was also an important parent radical of HO• in the presence of chloride, and chloride could effectively compensate the inhibitory effect of bicarbonate on HO• generation in the system. Moreover, reactions and rate constants in current models were scrutinized from corresponding literature, and the reaction rate constants of Cl2•- with bicarbonate and carbonate (kCl2•-, HCO3- and kCl2•-, CO32-) were reevaluated to be 1.47 × 105 and 3.78 × 106 M-1s-1, respectively, by laser flash photolysis. With the newly obtained rate constants, the refined model could accurately simulate concentrations of all three radicals under different chloride and bicarbonate dosages with satisfactory deviations (< 30 %). Meanwhile, the refined model performed much better in predicting pollutant degradation and radical contribution compared with the unrefined model (with the previously estimated kCl2•-, HCO3- and kCl2•-, CO32-). The results of this study enhanced the accuracy and applicability of the kinetic model of UV/NH2Cl, and deepened the understanding of radical transformation in the process.

Computational pathology: A survey review and the way forward.

Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field's future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.

Efficient conversion of propane in a microchannel reactor at ambient conditions.

The oxidative dehydrogenation of propane, primarily sourced from shale gas, holds promise in meeting the surging global demand for propylene. However, this process necessitates high operating temperatures, which amplifies safety concerns in its application due to the use of mixed propane and oxygen. Moreover, these elevated temperatures may heighten the risk of overoxidation, leading to carbon dioxide formation. Here we introduce a microchannel reaction system designed for the oxidative dehydrogenation of propane within an aqueous environment, enabling highly selective and active propylene production at room temperature and ambient pressure with mitigated safety risks. A propylene selectivity of over 92% and production rate of 19.57 mmol mCu-2 h-1 are simultaneously achieved. This exceptional performance stems from the in situ creation of a highly active, oxygen-containing Cu catalytic surface for propane activation, and the enhanced propane transfer via an enlarged gas-liquid interfacial area and a reduced diffusion path by establishing a gas-liquid Taylor flow using a custom-made T-junction microdevice. This microchannel reaction system offers an appealing approach to accelerate gas-liquid-solid reactions limited by the solubility of gaseous reactant.

ARTIFICIAL INTELLIGENCE FOR OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY-BASED DISEASE ACTIVITY PREDICTION IN AGE-RELATED MACULAR DEGENERATION.

PURPOSE: The authors hypothesize that optical coherence tomography angiography (OCTA)-visualized vascular morphology may be a predictor of choroidal neovascularization status in age-related macular degeneration (AMD). The authors thus evaluated the use of artificial intelligence (AI) to predict different stages of AMD disease based on OCTA en face 2D projections scans. METHODS: Retrospective cross-sectional study based on collected 2D OCTA data from 310 high-resolution scans. Based on OCT B-scan fluid and clinical status, OCTA was classified as normal, dry AMD, wet AMD active, and wet AMD in remission with no signs of activity. Two human experts graded the same test set, and a consensus grading between two experts was used for the prediction of four categories. RESULTS: The AI can achieve 80.36% accuracy on a four-category grading task with 2D OCTA projections. The sensitivity of prediction by AI was 0.7857 (active), 0.7142 (remission), 0.9286 (dry AMD), and 0.9286 (normal) and the specificity was 0.9524, 0.9524, 0.9286, and 0.9524, respectively. The sensitivity of prediction by human experts was 0.4286 active choroidal neovascularization, 0.2143 remission, 0.8571 dry AMD, and 0.8571 normal with specificity of 0.7619, 0.9286, 0.7857, and 0.9762, respectively. The overall AI classification prediction was significantly better than the human (odds ratio = 1.95, P = 0.0021). CONCLUSION: These data show that choroidal neovascularization morphology can be used to predict disease activity by AI; longitudinal studies are needed to better understand the evolution of choroidal neovascularization and features that predict reactivation. Future studies will be able to evaluate the additional predicative value of OCTA on top of other imaging characteristics (i.e., fluid location on OCT B scans) to help predict response to treatment.

ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model.

A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). However, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs, complicating the inference of tumor phylogenies. We introduce a new evolutionary model, the constrained k-Dollo model, that uses SNVs as phylogenetic markers but constrains losses of SNVs according to clusters of cells. We derive an algorithm, ConDoR, that infers phylogenies from targeted scDNA-seq data using this model. We demonstrate the advantages of ConDoR on simulated and real scDNA-seq data.

Construction of organic/GaN heterostructures for DUV-to-NIR broadband photodetection.

Herein, a broadband photodetector (BPD) is constructed with consistent and stable detection abilities for deep ultraviolet to near-infrared spectral range. The BPD integrates the GaN template with a hybrid organic semiconductor, PM6:Y6, via the spin-coating process, and is fabricated in the form of asymmetric metal-semiconductor-metal structure. Under an optimal voltage, the device shows consistent photoresponse within 254 to 850 nm, featuring high responsivity (10 to 60 A/W), photo-to-dark-current ratio over 103, and fast response time. These results show the potential of such organic/GaN heterojunctions as a simple and effective strategy to build BPDs for a reliable photo-sensing application in the future.

Hydrogen-bonded organic frameworks: new horizons in biomedical applications.

Hydrogen-bonded organic frameworks (HOFs) are an emerging attractive class of highly crystalline porous materials characterized by significant biocompatibility, rich chemical functionalities and well-defined porosity. The unique advantages including metal-free nature and reversible binding manner significantly distinguish HOFs from other porous materials in the biotechnology and biomedical field. However, the relevant HOF studies still remain in their infancy despite the promising and remarkable results that have been presented in recent years. Due to the intricate and dynamic nature of physiological conditions, the major challenge lies in the stability and structural diversity of HOFs in vivo. In this Tutorial Review, we summarize the common building blocks for the construction of HOF-based functional biomaterials and the latest developments in the biological field. Moreover, we highlight current challenges regarding the stability and functionalization of HOFs along with the corresponding potential solutions. This Tutorial Review will have a profound effect in future years on the design and applications of HOF-based biomaterials.

Simultaneous estimation of magnetic moment and Brownian relaxation time distributions of magnetic nanoparticles based on magnetic particle spectroscopy for biosensing application.

Magnetic nanoparticles (MNPs) exhibit unique physicochemical characteristics owing to their comparable dimensions with important biological substances, high surface-to-volume ratios, size-dependent magnetic properties, and temperature sensitivity. In this study, we present a novel method for simultaneously estimating the magnetic moment and Brownian relaxation time distribution of MNPs based on AC magnetization harmonics. We provide a detailed description of the theoretical framework and experimental procedures. The dynamics of MNP magnetization are described using the Fokker-Planck equation, and a matrix equation is established to connect the magnetic moment, Brownian relaxation time, and magnetization harmonics. By employing a non-negative linear least squares algorithm with constraints, the magnetic moment and Brownian relaxation time distributions are inversed, which are then converted into the distributions of core sizes and hydrodynamic sizes. Finally, the estimated core size distribution reconstructed from M-H curves is consistent with the hydrodynamic size distribution measured by dynamic light scattering. This method is particularly useful for facilitating quantitative magnetic immunoassays.

Spin Coherence and Spin Relaxation in Hybrid Organic-Inorganic Lead and Mixed Lead-Tin Perovskites.

Metal halide perovskites make up a promising class of materials for semiconductor spintronics. Here we report a systematic investigation of coherent spin precession, spin dephasing and spin relaxation of electrons and holes in two hybrid organic-inorganic perovskites MA0.3FA0.7PbI3 and MA0.3FA0.7Pb0.5Sn0.5I3 using time-resolved Faraday rotation spectroscopy. With applied in-plane magnetic fields, we observe robust Larmor spin precession of electrons and holes that persists for hundreds of picoseconds. The spin dephasing and relaxation processes are likely to be sensitive to the defect levels. Temperature-dependent measurements give further insights into the spin relaxation channels. The extracted electron Landé g-factors (3.75 and 4.36) are the biggest among the reported values in inorganic or hybrid perovskites. Both the electron and hole g-factors shift dramatically with temperature, which we propose to originate from thermal lattice vibration effects on the band structure. These results lay the foundation for further design and use of lead- and tin-based perovskites for spintronic applications.

Enhanced hydroxyl radical generation for micropollutant degradation in the In2O3/Vis-LED process through the addition of periodate.

Periodate (PI) as an oxidant has been extensively studied for organic foulants removal in advanced oxidation processes. Here PI was introduced into In2O3/Vis-LED process to enhance the formation of ·OH for promoting the degradation of organic foulants. Results showed that the addition of PI would significantly promote the removal of sulfamethoxazole (SMX) in the In2O3/Vis-LED process (from 9.26% to 100%), and ·OH was proved to be the dominant species in the system. Besides, the process exhibited non-selectivity in the removal of different organic foulants. Comparatively, various oxidants (e.g., peroxymonosulfate, peroxydisulfate, and hydrogen peroxide) did not markedly promote the removal of SMX in the In2O3/Vis-LED process. Electrochemical analyses demonstrated that PI could effectively receive photoelectrons, thus inhibiting the recombination of photogenerated electron-hole (e-/h+) pairs. The holes then oxidized the adsorbed H2O to generate ·OH, and the PI converted to iodate at the same time. Additionally, the removal rate of SMX reduced from 100% to 17.2% as Vis-LED wavelengths increased from 440 to 560 nm, because of the low energy of photons produced at longer wavelengths. Notably, the species of PI do not affect its ability to accept electrons, resulting in the degradation efficiency of SMX irrespective of pH (4.0-10.0). The coexistence of inorganic cations and anions (such as Cl-, CO32-/HCO3-, SO42-, Ca2+, and Mg2+) also had an insignificant effect on SMX degradation. Furthermore, the process also showed excellent degradation potential in real water. The proposed strategy provides a new insight for visible light-catalyzed activation of PI and guidance to explore green catalytic processes for high-efficiency removal of various organic foulants.

A narrative review about CDK4/6 inhibitors in the setting of drug resistance: updates on biomarkers and therapeutic strategies in breast cancer.

Background and Objective: Previous studies have demonstrated that cyclin-dependent kinase 4/6 (CDK4/6) inhibitors combined with endocrine therapy are able to effectively improve the prognosis of hormone receptor positive (HR+), human epidermal growth factor receptor 2 (HER2) negative advanced breast cancer (ABC). Five CDK4/6 inhibitors, palbociclib, ribociclib, abemaciclib, dalpiciclib, and trilaciclib have been approved for the treatment of this breast cancer subset at present. The efficacy and safety profile of adding these CDK4/6 inhibitors to endocrine therapies in HR+ breast cancer has been proved in a number of clinical trials. Besides, extending the application of CDK4/6 inhibitors to HER2+ or triple negative breast cancers (TNBCs) has also led to some clinical benefits. Methods: A comprehensive, non-systematic review of the latest literature about CDK4/6 inhibitors resistance in breast cancer was conducted. The examined database was PubMed/MEDLINE, and the last search was run on October 1, 2022. Key Content and Findings: In this review, the generation of CDK4/6 inhibitors resistance is related to gene alteration, pathway dysregulation, and tumor microenvironment change. With a deeper insight in the mechanisms of CDK4/6 inhibitor resistance, some biomarkers have presented the potential to predict drug resistance and showed prognostic value. Furthermore, in preclinical studies, some modified treatment strategies based on CDK4/6 inhibitors exhibited effectiveness on drug-resistant tumors, suggesting a preventable or reversible drug-resistant status. Conclusions: This review clarified the current knowledge about mechanisms, the biomarkers to overcome the drug resistance of CDK4/6 inhibitors, and the latest clinical progresses about CDK4/6 inhibitors. Possible approaches to overcome CDK4/6 inhibitors resistance were further discussed. For example, using another CDK4/6 inhibitor, PI3K inhibitor, mTOR inhibitor, or a novel drug.

Nitrilotriacetic acid-assisted Mn(II) activated periodate for rapid and long-lasting degradation of carbamazepine: The importance of Mn(IV)-oxo species.

Periodate-based (PI, IO4-) oxidation processes for pollutant elimination have gained increased attention in recent years. This study shows that nitrilotriacetic acid (NTA) can assist trace Mn(II) in activating PI for fast and long-lasting degradation of carbamazepine (CBZ) (100% degradation in 2 min). PI can oxidize Mn(II) to permanganate(MnO4-, Mn(VII)) in the presence of NTA, which indicates the important role of transient manganese-oxo species. 18O isotope labeling experiments using methyl phenyl sulfoxide (PMSO) as a probe further confirmed the formation of manganese-oxo species. The chemical stoichiometric relationship (PI consumption: PMSO2 generation) and theoretical calculation suggested that Mn(IV)-oxo-NTA species were the main reactive species. The NTA-chelated manganese facilitated direct oxygen transfer from PI to Mn(II)-NTA and prevented hydrolysis and agglomeration of transient manganese-oxo species. PI was transformed completely to stable and nontoxic iodate but not lower-valent toxic iodine species (i.e., HOI, I2, and I-). The degradation pathways and mechanisms of CBZ were investigated using mass spectrometry and density functional theory (DFT) calculation. This study provided a steady and highly efficient choice for the quick degradation of organic micropollutants and broadened the perspective on the evolution mechanism of manganese intermediates in the Mn(II)/NTA/PI system.

Biodegradable composites of poly(propylene carbonate) mixed with silicon nitride for osteogenic activity of adipose-derived stem cells and repair of bone defects.

Absorbable polymers have attracted increasing attention in the field of bone regeneration in recent years for their degradation. Compared with other degradable polymers, polypropylene carbonate (PPC) has several advantages such as biodegradation and relatively cheap raw materials. Most importantly, PPC can degrade into water and carbon dioxide totally which does not give rise to local inflammation and bone resorption in vivo. However, pure PPC has not presented excellent osteoinductivity properties. In order to enhance the osteoinductivity of PPC, silicon nitride (SiN) was employed due to its excellent mechanical properties, biocompatibility and osteogenesis compared with the other common materials such as hydroxyapatite and calcium phosphate ceramics. In this study, composites of PPC mixed with different contents of SiN were prepared successfully (PSN10 with 10 wt% SiN content, and PSN20 with 20 wt% SiN content). The characterization of the composites suggested that PPC mixed with SiN evenly and PSN composites presented stable properties. The results in vitro revealed that the PSN20 composite possessed satisfactory biocompatibility and exerted better osteogenic differentiation effects on adipose-derived stem cells (ADSCs). In particular, the PSN20 composite accelerated the healing of bone defects better and degraded with the process of bone healing in vivo. Overall, the PSN20 composite exhibited better biocompatibility, induced osteogenic differentiation of ADSCs and promoted healing of bone defects, due to which the PSN composite is considered as a potential candidate for treating bone defects in the field of bone tissue engineering.

Heterogeneous organization of Locus coeruleus: An intrinsic mechanism for functional complexity.

Locus coeruleus (LC) is a small nucleus located deep in the brainstem that contains the majority of central noradrenergic neurons, which provide the primary source of noradrenaline (NA) throughout the entire central nervous system (CNS).The release of neurotransmitter NA is considered to modulate arousal, sensory processing, attention, aversive and adaptive stress responses as well as high-order cognitive function and memory, with the highly ramified axonal arborizations of LC-NA neurons sending wide projections to the targeted brain areas. For over 30 years, LC was thought to be a homogeneous nucleus in structure and function due to the widespread uniform release of NA by LC-NA neurons and simultaneous action in several CNS regions, such as the prefrontal cortex, hippocampus, cerebellum, and spinal cord. However, recent advances in neuroscience tools have revealed that LC is probably not so homogeneous as we previous thought and exhibits heterogeneity in various aspects. Accumulating studies have shown that the functional complexity of LC may be attributed to its heterogeneity in developmental origin, projection patterns, topography distribution, morphology and molecular organization, electrophysiological properties and sex differences. This review will highlight the heterogeneity of LC and its critical role in modulating diverse behavioral outcomes.

Broadband electrically controlled reflective metasurface for reconfigurable circularly polarized wavefront manipulation.

A broadband, electrically controlled, reconfigurable, circularly polarized reflective metasurface is presented. The chirality of the metasurface structure is changed by switching active elements, which benefits from the tunable current distributions generated by the elaborately designed structure under x-polarized and y-polarized waves. Notably, the proposed metasurface unit cell maintains a good circular-polarization efficiency in a broadband range of 6.82-9.96 GHz (fractional bandwidth of 37%) with a phase difference of π between the two states. As a demonstration, a reconfigurable circularly polarized metasurface containing 8 × 8 elements was simulated and measured. The results verify that the proposed metasurface can flexibly control circularly polarized waves in a broadband, realizing beam splitting, mirror reflection, and other beam manipulations from 7.4 GHz to 9.9 GHz (fractional bandwidth of 28.9%) by simply adjusting the loaded active elements. The proposed reconfigurable metasurface may offer a promising approach to electromagnetic wave manipulation or communication systems.

Mechanical Characterization and Constitutive Modeling of Nano-Stabilized Soil under Uniaxial Compression.

The stress-strain constitutive model under uniaxial compression is a basic element and important characterization method for determining physical and mechanical properties in cement-based materials research. In this study, a stress-strain constitutive model under uniaxial compression was established, which was based on a new nano-stabilized soil (NSS) through typical mechanical tests and constitutive relationship research. The results indicate that the unconfined compressive strength (UCS) of the nano-stabilized soil was enhanced with the increase in curing period and nano-stabilizer dosage, and that the strength growth rate reaches the maximum at a 12% dosage in the tested samples. The UCS of NSS under a 12% dosage is about 10~15% higher than that of ordinary stabilized soil (SS) without nano doping, and 25~40% higher compared with grade 42.5 cement-soil. The established constitutive model could accurately describe the linear-elastic and elastic-plastic deformation characteristics of NSS under uniaxial compression, which will be conducive to revealing the curve variation law of the stress-strain process. The research results could provide scientific support for the theoretical innovation and engineering application of green environmental protection materials.

Phloretin decreases microglia-mediated synaptic engulfment to prevent chronic mild stress-induced depression-like behaviors in the mPFC.

Background: Stress is an important risk factor to induce psychiatric disorders such as depression. Phloretin (PHL), a natural dihydrochalcone compound, has been shown to exhibit anti-inflammatory and anti-oxidative effects. However, the impact of PHL on the depression and the underlying mechanism remain unclear. Methods: The animal behavior tests were used to determine the protective of PHL on the chronic mild stress (CMS)-induced depression-like behaviors. The Magnetic Resonance Imaging (MRI), electron microscopy analysis, fiber photometry, electrophysiology, and Structure Illumination Microscopy (SIM) were used to investigate the protective of PHL on the structural and functional impairments induced by CMS exposure in the mPFC. The RNA sequencing, western blot, reporter gene assay, and chromatin immunoprecipitation were adopted to investigate the mechanisms. Results: We showed that PHL efficiently prevented the CMS-induced depressive-like behaviors. Moreover, PHL not only attenuated the decrease of synapse losses but also improved the dendritic spine density and neuronal activity in the mPFC after CMS exposure. Furthermore, PHL remarkably inhibited the CMS-induced microglial activation and phagocytic activity in the mPFC. In addition, we demonstrated that PHL decreased the CMS-induced synapse losses by inhibiting the deposition of complement C3 deposition onto synapses and subsequent microglia-mediated synaptic engulfment. Finally, we revealed that PHL inhibited the NF-κB-C3 axis to display neuroprotective effects. Conclusions: Our results indicate that PHL represses the NF-κB-C3 axis and subsequent microglia-mediated synaptic engulfment to protect against CMS-induced depression in the mPFC.

Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer.

Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.

ConDoR: Tumor phylogeny inference with a copy-number constrained mutation loss model.

Tumors consist of subpopulations of cells that harbor distinct collections of somatic mutations. These mutations range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). While many approaches infer tumor phylogenies using SNVs as phylogenetic markers, CNAs that overlap SNVs may lead to erroneous phylogenetic inference. Specifically, an SNV may be lost in a cell due to a deletion of the genomic segment containing the SNV. Unfortunately, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs. For instance, recent targeted scDNA-seq technologies, such as Mission Bio Tapestri, measure SNVs with high fidelity in individual cells, but yield much less reliable measurements of CNAs. We introduce a new evolutionary model, the constrained k-Dollo model, that uses SNVs as phylogenetic markers and partial information about CNAs in the form of clustering of cells with similar copy-number profiles. This copy-number clustering constrains where loss of SNVs can occur in the phylogeny. We develop ConDoR (Constrained Dollo Reconstruction), an algorithm to infer tumor phylogenies from targeted scDNA-seq data using the constrained k-Dollo model. We show that ConDoR outperforms existing methods on simulated data. We use ConDoR to analyze a new multi-region targeted scDNA-seq dataset of 2153 cells from a pancreatic ductal adenocarcinoma (PDAC) tumor and produce a more plausible phylogeny compared to existing methods that conforms to histological results for the tumor from a previous study. We also analyze a metastatic colorectal cancer dataset, deriving a more parsimonious phylogeny than previously published analyses and with a simpler monoclonal origin of metastasis compared to the original study. Code availability: Software is available at https://github.com/raphael-group/constrained-Dollo.