Loss of Katnal2 leads to ependymal ciliary hyperfunction and autism-related phenotypes in mice.

Autism spectrum disorders (ASD) frequently accompany macrocephaly, which often involves hydrocephalic enlargement of brain ventricles. Katnal2 is a microtubule-regulatory protein strongly linked to ASD, but it remains unclear whether Katnal2 knockout (KO) in mice leads to microtubule- and ASD-related molecular, synaptic, brain, and behavioral phenotypes. We found that Katnal2-KO mice display ASD-like social communication deficits and age-dependent progressive ventricular enlargements. The latter involves increased length and beating frequency of motile cilia on ependymal cells lining ventricles. Katnal2-KO hippocampal neurons surrounded by enlarged lateral ventricles show progressive synaptic deficits that correlate with ASD-like transcriptomic changes involving synaptic gene down-regulation. Importantly, early postnatal Katnal2 re-expression prevents ciliary, ventricular, and behavioral phenotypes in Katnal2-KO adults, suggesting a causal relationship and a potential treatment. Therefore, Katnal2 negatively regulates ependymal ciliary function and its deletion in mice leads to ependymal ciliary hyperfunction and hydrocephalus accompanying ASD-related behavioral, synaptic, and transcriptomic changes.

CYFIP2 p.Arg87Cys Causes Neurological Defects and Degradation of CYFIP2.

Here, we report the generation and comprehensive characterization of a knockin mouse model for the hotspot p.Arg87Cys variant of the cytoplasmic FMR1-interacting protein 2 (CYFIP2) gene, which was recently identified in individuals diagnosed with West syndrome, a developmental and epileptic encephalopathy. The Cyfip2+/R87C mice recapitulated many neurological and neurobehavioral phenotypes of the patients, including spasmlike movements, microcephaly, and impaired social communication. Age-progressive cytoarchitectural disorganization and gliosis were also identified in the hippocampus of Cyfip2+/R87C mice. Beyond identifying a decrease in CYFIP2 protein levels in the Cyfip2+/R87C brains, we demonstrated that the p.Arg87Cys variant enhances ubiquitination and proteasomal degradation of CYFIP2. ANN NEUROL 2023;93:155-163.

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.

BACKGROUND: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. METHODS: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP). RESULTS: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. CONCLUSION: Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data.

We propose a machine learning framework for the data-driven discovery of macroscopic chemotactic Partial Differential Equations (PDEs)-and the closures that lead to them- from high-fidelity, individual-based stochastic simulations of Escherichia coli bacterial motility. The fine scale, chemomechanical, hybrid (continuum-Monte Carlo) simulation model embodies the underlying biophysics, and its parameters are informed from experimental observations of individual cells. Using a parsimonious set of collective observables, we learn effective, coarse-grained "Keller-Segel class" chemotactic PDEs using machine learning regressors: (a) (shallow) feedforward neural networks and (b) Gaussian Processes. The learned laws can be black-box (when no prior knowledge about the PDE law structure is assumed) or gray-box when parts of the equation (e.g. the pure diffusion part) is known and "hardwired" in the regression process. More importantly, we discuss data-driven corrections (both additive and functional), to analytically known, approximate closures.

Fine-Tuning a Robust Metal-Organic Framework toward Enhanced Clean Energy Gas Storage.

The development of adsorbents with molecular precision offers a promising strategy to enhance storage of hydrogen and methane─considered the fuel of the future and a transitional fuel, respectively─and to realize a carbon-neutral energy cycle. Herein we employ a postsynthetic modification strategy on a robust metal-organic framework (MOF), MFU-4l, to boost its storage capacity toward these clean energy gases. MFU-4l-Li displays one of the best volumetric deliverable hydrogen capacities of 50.2 g L-1 under combined temperature and pressure swing conditions (77 K/100 bar → 160 K/5 bar) while maintaining a moderately high gravimetric capacity of 9.4 wt %. Moreover, MFU-4l-Li demonstrates impressive methane storage performance with a 5-100 bar usable capacity of 251 cm3 (STP) cm-3 (0.38 g g-1) and 220 cm3 (STP) cm-3 (0.30 g g-1) at 270 and 296 K, respectively. Notably, these hydrogen and methane storage capacities are significantly improved compared to those of its isoreticular analogue, MFU-4l, and place MFU-4l-Li among the best MOF-based materials for this application.

Phase Transitions in Metal-Organic Frameworks Directly Monitored through In Situ Variable Temperature Liquid-Cell Transmission Electron Microscopy and In Situ X-ray Diffraction.

Zr6-based metal-organic frameworks (MOFs) with tetratopic organic linkers have been extensively investigated owing to their versatile structural tunability. While diverse topologies and polymorphism in the resulting MOFs are often encountered with tetratopic linkers and Zr6 nodes, reports on phase transitions within these systems are rare. Thus, we have a limited understanding of polymorph transformations, hindering the rational development of pure phase materials. In this study, a phase transition from a microporous MOF, scu-NU-906, to a mesoporous MOF, csq-NU-1008, was discovered and monitored through in situ variable temperature liquid-cell transmission electron microscopy (VT-LCTEM), high-resolution transmission electron microscopy (HRTEM), and in situ variable temperature powder X-ray diffraction (VT-PXRD). It was found that the microporous- to-mesoporous transformation in the presence of formic acid occurs via a concomitant dissolution-reprecipitation process.

Structural Diversity of Zirconium Metal-Organic Frameworks and Effect on Adsorption of Toxic Chemicals.

While linkers with various conformations pose challenges in the design and prediction of metal-organic framework (MOF) structures, they ultimately provide great opportunities for the discovery of novel structures thereby enriching structural diversity. Tetratopic carboxylate linkers, for example, have been widely used in the formation of Zr-based MOFs due to the ability to target diverse topologies, providing a promising platform to explore their mechanisms of formation. However, it remains a challenge to control the resulting structures when considering the complex assembly of linkers with unpredicted conformations and diverse Zr6 node connectivities. Herein, we systematically explore how solvents and modulators employed during synthesis influence the resulting topologies of Zr-MOFs, choosing H4TCPB-Br2 (1,4-dibromo-2,3,5,6-tetrakis(4-carboxyphenyl)benzene) as a representative tetratopic carboxylate linker. By modulating the reaction conditions, the conformations of the linker and the connectivities of the Zr6 node can be simultaneously tuned, resulting in four types of structures: a new topology (NU-500), she (NU-600), scu (NU-906), and csq (NU-1008). Importantly, we have synthesized the first 5-connected Zr6 node to date with the (4,4,4,5)-connected framework, NU-500. We subsequently performed detailed structural analyses to uncover the relationship between the structures and topologies of these MOFs and demonstrated the crucial role that the flexible linker played to access varied structures by different degrees of linker deformation. Due to a variety of pore structures ranging from micropores to hierarchical micropores and mesopores, the resulting MOFs show drastically different behaviors for the adsorption of n-hexane and dynamic adsorption of 2-chloroethyl ethyl sulfide (CEES) under dry and humid conditions.

Coarse-scale PDEs from fine-scale observations via machine learning.

Complex spatiotemporal dynamics of physicochemical processes are often modeled at a microscopic level (through, e.g., atomistic, agent-based, or lattice models) based on first principles. Some of these processes can also be successfully modeled at the macroscopic level using, e.g., partial differential equations (PDEs) describing the evolution of the right few macroscopic observables (e.g., concentration and momentum fields). Deriving good macroscopic descriptions (the so-called "closure problem") is often a time-consuming process requiring deep understanding/intuition about the system of interest. Recent developments in data science provide alternative ways to effectively extract/learn accurate macroscopic descriptions approximating the underlying microscopic observations. In this paper, we introduce a data-driven framework for the identification of unavailable coarse-scale PDEs from microscopic observations via machine-learning algorithms. Specifically, using Gaussian processes, artificial neural networks, and/or diffusion maps, the proposed framework uncovers the relation between the relevant macroscopic space fields and their time evolution (the right-hand side of the explicitly unavailable macroscopic PDE). Interestingly, several choices equally representative of the data can be discovered. The framework will be illustrated through the data-driven discovery of macroscopic, concentration-level PDEs resulting from a fine-scale, lattice Boltzmann level model of a reaction/transport process. Once the coarse evolution law is identified, it can be simulated to produce long-term macroscopic predictions. Different features (pros as well as cons) of alternative machine-learning algorithms for performing this task (Gaussian processes and artificial neural networks) are presented and discussed.

Cell-Type-Specific Shank2 Deletion in Mice Leads to Differential Synaptic and Behavioral Phenotypes.

Shank2 is an excitatory postsynaptic scaffolding protein implicated in synaptic regulation and psychiatric disorders including autism spectrum disorders. Conventional Shank2-mutant (Shank2-/-) mice display several autistic-like behaviors, including social deficits, repetitive behaviors, hyperactivity, and anxiety-like behaviors. However, cell-type-specific contributions to these behaviors have remained largely unclear. Here, we deleted Shank2 in specific cell types and found that male mice lacking Shank2 in excitatory neurons (CaMKII-Cre;Shank2fl/fl) show social interaction deficits and mild social communication deficits, hyperactivity, and anxiety-like behaviors. In particular, male mice lacking Shank2 in GABAergic inhibitory neurons (Viaat-Cre;Shank2fl/fl) display social communication deficits, repetitive self-grooming, and mild hyperactivity. These behavioral changes were associated with distinct changes in hippocampal and striatal synaptic transmission in the two mouse lines. These results indicate that cell-type-specific deletions of Shank2 in mice lead to differential synaptic and behavioral abnormalities.SIGNIFICANCE STATEMENT Shank2 is an abundant excitatory postsynaptic scaffolding protein implicated in the regulation of excitatory synapses and diverse psychiatric disorders including autism spectrum disorders. Previous studies have reported in vivo functions of Shank2 mainly using global Shank2-null mice, but it remains largely unclear how individual cell types contribute to Shank2-dependent regulation of neuronal synapses and behaviors. Here, we have characterized conditional Shank2-mutant mice carrying the Shank2 deletion in excitatory and inhibitory neurons. These mouse lines display distinct alterations of synaptic transmission in the hippocampus and striatum that are associated with differential behavioral abnormalities in social, repetitive, locomotor, and anxiety-like domains.

Levels of vitamin D-associated cytokines distinguish between active and latent tuberculosis following a tuberculosis outbreak.

BACKGROUND: Vitamin D levels are associated with the extent of mycobactericidal activity. Interleukin (IL)-15 and IL-32 play roles in the vitamin D-mediated tuberculosis (TB) defense mechanism. Vitamin D induces IL-1ß, which plays an important role in terms of resistance to TB. We evaluated whether the levels of vitamin D-related cytokines distinguished between those with active TB and latent TB infection (LTBI). METHODS: In total, 50 TB-infected patients (25 with active TB and 25 with LTBI following a TB outbreak in a high school) were enrolled. Plasma 25-hydroxyvitamin D (25[OH]D), IL-15, IL-32, and IL-1ß levels were measured via enzyme-linked immunosorbent assays. Mycobacterium tuberculosis-specific antigen-induced and unstimulated cytokine levels were measured in the supernatants of the QuantiFERON TB Gold-In-Tube (QFT-GIT) assay. RESULTS: Plasma 25(OH)D and plasma IL-15 levels were lower in patients with active TB than in LTBI subjects (25(OH)D: 16.64 ng/mL vs. 21.6 ng/mL, P = 0.031; IL-15: 148.9 pg/mL vs. 189.8 pg/mL, P = 0.013). Plasma 25(OH)D levels correlated with the plasma levels of IL-15 and IL-1ß in TB-infected patients. In addition, the plasma 25(OH)D levels correlated positively with the level of unstimulated IL-15 (IL-15nil) and negatively with that of TB antigen-stimulated IL-32 (IL-32TB) in QFT-GIT supernatants. Although the IL-15nil and IL-15TB levels were higher in LTBI subjects than patients with active TB, the IL-32nil and IL-32TB levels were higher in the latter patients. A combination of the IL-15nil and IL-32TB levels accurately predicted 91.3% of active TB patients and latent subjects, with an area under the curve of 0.964. CONCLUSIONS: Our preliminary data showed that the levels of the vitamin D-related cytokines IL-15 and IL-32 differed between active TB patients and LTBI subjects. This result might be used as a basic data for developing biomarkers distinguishing between active TB and LTBI.

Selective nitrogen capture by porous hybrid materials containing accessible transition metal ion sites.

Selective dinitrogen binding to transition metal ions mainly covers two strategic domains: biological nitrogen fixation catalysed by metalloenzyme nitrogenases, and adsorptive purification of natural gas and air. Many transition metal-dinitrogen complexes have been envisaged for biomimetic nitrogen fixation to produce ammonia. Inspired by this concept, here we report mesoporous metal-organic framework materials containing accessible Cr(III) sites, able to thermodynamically capture N2 over CH4 and O2. This fundamental study integrating advanced experimental and computational tools confirmed that the separation mechanism for both N2/CH4 and N2/O2 gas mixtures is driven by the presence of these unsaturated Cr(III) sites that allows a much stronger binding of N2 over the two other gases. Besides the potential breakthrough in adsorption-based technologies, this proof of concept could open new horizons to address several challenges in chemistry, including the design of heterogeneous biomimetic catalysts through nitrogen fixation.

Exposure to volatile organic compounds and airway inflammation.

BACKGROUND: Exposure to low levels of volatile organic compounds (VOCs) in ordinary life is suspected to be related to oxidative stress and decreased lung function. This study evaluated whether exposure to ambient VOCs in indoor air affects airway inflammation. METHODS: Thirty-four subjects from the hospital that had moved to a new building were enrolled. Symptoms of sick building syndrome, pulmonary function tests, and fractional exhaled nitric oxide (FeNO) were evaluated, and random urine samples were collected 1 week before and after the move. Urine samples were analyzed for VOC metabolites, oxidative stress biomarkers, and urinary leukotriene E4 (uLTE4) levels. RESULTS: The level of indoor VOCs in the new building was higher than that in the old building. Symptoms of eye dryness and eye irritation, as well as the level of a xylene metabolite (o-methylhippuric acid) increased after moving into the new building (p = 0.012, p = 0.008, and p < 0.0001, respectively). For the inflammatory markers, FeNO decreased (p = 0.012 and p = 0.04, respectively) and the uLTE4 level increased (p = 0.005) after the move. CONCLUSION: Exposure to a higher level of VOCs in everyday life could affect airway inflammation.

Plasma CRABP2 as a Novel Biomarker in Patients with Non-Small Cell Lung Cancer.

BACKGROUND: Lung cancer is the most common cause of cancer-related mortality worldwide. We previously reported the identification of a new genetic marker, cellular retinoic acid binding protein 2 (CRABP2), in lung cancer tissues. The aim of this study was to assess plasma levels of CRABP2 from patients with non-small cell lung cancer (NSCLC). METHODS: Blood samples that were collected from 122 patients with NSCLC between September 2009 and September 2013 were selected for the analysis, along with samples from age- (± 5 years), sex-, and cigarette smoking history (± 10 pack-years [PY])-matched controls from the Korea Biobank Network. The control specimens were from patients who were without malignancies or pulmonary diseases. We measured plasma levels of CRABP2 using commercially available enzyme-linked immunosorbent assay kits. RESULTS: The mean age of the NSCLC patients was 71.8 ± 8.9 years, and the median cigarette smoking history was 32 PY (range, 0-150 PY). Plasma CRABP2 levels were significantly higher in patients with NSCLC than in the matched controls (37.63 ± 28.71 ng/mL vs. 24.09 ± 21.09 ng/mL, P < 0.001). Higher plasma CRABP2 levels were also correlated with lower survival rates in NSCLC patients (P = 0.014). CONCLUSION: Plasma CRABP2 levels might be a novel diagnostic and prognostic marker in NSCLC.

Enhanced Neuronal Activity in the Medial Prefrontal Cortex during Social Approach Behavior.

UNLABELLED: Although the medial prefrontal cortex (mPFC) is known to play a crucial role in rodent social behavior, little is known about mPFC neural correlates of social behavior. In the present study, we examined single-neuron activity in the mPFC of mice performing a modified version of the three-chamber test. We found that a subset of mPFC neurons elevate discharge rates when approaching a stranger mouse but not when approaching an inanimate object or an empty chamber. Our results reveal mPFC neural activity that is correlated with social approach behavior in a widely used social-interaction paradigm. These findings might be helpful for future investigations of mPFC neural processes underlying social interaction in health and disease. SIGNIFICANCE STATEMENT: Although the prefrontal cortex is known to play a crucial role in rodent social behavior, little is known about prefrontal neural correlates of social behavior. This study shows that the activity of a subset of prefrontal neurons increases in association with social approach behavior during a three-chamber test-a widely used behavioral paradigm. Such responses might be a signature of prefrontal neural processes underlying social approach behavior.

A cluster analysis of chronic obstructive pulmonary disease in dusty areas cohort identified three subgroups.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable clinical manifestations, structural changes, and treatment responses. In a cohort study, we performed a baseline cluster analysis to identify the subgroups of COPD and to assess the clinical outcomes of each subgroup during a 1-year follow-up. METHODS: We analyzed dusty areas cohort comprising 272 patients with COPD. The main factors with the highest loading in 15 variables were selected using principal component analysis (PCA) at baseline. The COPD patients were classified by hierarchical cluster analysis using clinical, physiological, and imaging data based on PCA-transformed data. The clinical parameters and outcomes during the 1-year follow-up were evaluated among the subgroups. RESULTS: PCA revealed that six independent components accounted for 77.3% of variance. Three distinct subgroups were identified through the cluster analysis. Subgroup 1 included younger subjects with fewer symptoms and mild airflow obstruction, and they had fewer exacerbations during the 1-year follow-up. Subgroup 2 comprised subjects with additional symptoms and moderate airflow obstruction, and they most frequently experienced exacerbations requiring hospitalization during the 1-year follow-up. Subgroup 3 included subjects with additional symptoms and mild airflow obstruction; this group had more female patients and a modest frequency of exacerbations requiring hospitalization. CONCLUSIONS: Cluster analysis using the baseline data of a COPD cohort identified three distinct subgroups with different clinical parameters and outcomes. These findings suggest that the identified subgroups represent clinically meaningful subtypes of COPD.

Paracrine influence of human perivascular cells on the proliferation of adenocarcinoma alveolar epithelial cells.

Understanding the crosstalk mechanisms between perivascular cells (PVCs) and cancer cells might be beneficial in preventing cancer development and metastasis. In this study, we investigated the paracrine influence of PVCs derived from human umbilical cords on the proliferation of lung adenocarcinoma epithelial cells (A549) and erythroleukemia cells (TF-1α and K562) in vitro using Transwell® co-culture systems. PVCs promoted the proliferation of A549 cells without inducing morphological changes, but had no effect on the proliferation of TF-1α and K562 cells. To identify the factors secreted from PVCs, conditioned media harvested from PVC cultures were analyzed by antibody arrays. We identified a set of cytokines, including persephin (PSPN), a neurotrophic factor, and a key regulator of oral squamous cell carcinoma progression. Supplementation with PSPN significantly increased the proliferation of A549 cells. These results suggested that PVCs produced a differential effect on the proliferation of cancer cells in a cell-type dependent manner. Further, secretome analyses of PVCs and the elucidation of the molecular mechanisms could facilitate the discovery of therapeutic target(s) for lung cancer.

Comparison of serum biomarkers between patients with asthma and with chronic obstructive pulmonary disease.

OBJECTIVE: Asthma and chronic obstructive pulmonary disease (COPD) have distinct pathophysiological mechanisms but sometimes share similar clinical manifestations. Distinguishing between these diseases is important. This study compared the profiles of serum biomarkers between patients with asthma and those with COPD. METHODS: Serum levels of the chitinase like protein YKL-40, periostin, interleukin (IL)-18, and chemokine (C--C motif) ligand 18 (CCL18) were measured in asthma patients (n = 20), COPD patients (n = 16), and normal controls (n = 20). RESULTS: Serum levels of YKL-40 were higher in COPD patients [median (range), 55 (17-565) versus 208 (74-922) ng/mL, p < 0.0001], but no differences were observed between asthma and COPD patients after adjusting for age and forced expiratory volume in 1 s (FEV1). No differences in serum levels of periostin, IL-18, or CCL18 were observed between the patient groups. Total IgE and airway hypersensitivity were negatively correlated (r = -0.485, p = 0.007). CCL18 levels were related to patients' age in asthmatic patients (r = -0.562, p = 0.010). Serum levels of CCL18 and IL-18 were positively correlated in patients with COPD (r = 0.696, p = 0.003). CONCLUSIONS: No differences in the serum profiles of periostin, IL-18, or CCL18 were observed between patients with asthma and those with COPD. Serum levels of YKL-40 were not different between asthma and COPD patients after adjusting for age and FEV1. There were negative correlation between CCL18 and age in patients with asthma and positive correlation between IL-18 and CCL18 in patients with COPD.

Position and Velocity Estimation for Two-Inertia System with Nonlinear Stiffness Based on Acceleration Sensor.

In this paper, we consider the state estimation problem for flexible joint manipulators that involve nonlinear characteristics in their stiffness. The two key ideas of our design are that (a) an accelerometer is used in order that the estimation error dynamics do not depend on nonlinearities at the link part of the manipulators and (b) the model of the nonlinear stiffness is indeed a Lipschitz function. Based on the measured acceleration, we propose a nonlinear observer under the Lipschitz condition of the nonlinear stiffness. In addition, in order to effectively compensate for the estimation error, the gain of the proposed observer is chosen from the ARE (algebraic Riccati equations) which depend on the Lipschitz constant. Comparative experimental results verify the effectiveness of the proposed method.

Immunolocalisation and oestrogen regulation of small proline-rich protein 2a protein in the mouse uterus.

Small proline-rich protein 2a (Sprr2a) is one of the structural components of the cornified keratinocyte cell envelope that contributes to form a protective barrier in the skin against dehydration and environmental stress. Interestingly, Sprr2a mRNA is detected in the mouse uterus and is regulated by 17ß-oestradiol (E2). In the present study, we investigated the effects of E2 and oestrogenic compounds on the regulation and localisation of Sprr2a protein in the mouse uterus. Immunohistochemical staining revealed that Sprr2a protein is detected only in the adult uterus, and not in the ovary, oviduct or testis. We also demonstrated that Sprr2a protein is tightly regulated by E2 in the mouse uterus and exclusively detected in luminal and glandular epithelial cells. Furthermore, Sprr2a is dose-dependently induced by oestrogenic compounds such as bisphenol A and 4-tert-octylphenol. Collectively, our studies suggest that Sprr2a protein may have a unique function in physiological events in the mouse uterus and can be used as an indicator to detect compounds with oestrogenic activity in the mouse uterus.

Development and characterization of a round hand-held silicon photomultiplier based gamma camera for intraoperative imaging.

This paper describes the development of a hand-held gamma camera for intraoperative surgical guidance that is based on silicon photomultiplier (SiPM) technology. The camera incorporates a cerium doped lanthanum bromide (LaBr3:Ce) plate scintillator, an array of 80 SiPM photodetectors and a two-layer parallel-hole collimator. The field of view is circular with a 60 mm diameter. The disk-shaped camera housing is 75 mm in diameter, approximately 40.5 mm thick and has a mass of only 1.4 kg, permitting either hand-held or arm-mounted use. All camera components are integrated on a mobile cart that allows easy transport. The camera was developed for use in surgical procedures including determination of the location and extent of primary carcinomas, detection of secondary lesions and sentinel lymph node biopsy (SLNB). Here we describe the camera design and its principal operating characteristics, including spatial resolution, energy resolution, sensitivity uniformity, and geometric linearity. The gamma camera has an intrinsic spatial resolution of 4.2 mm FWHM, an energy resolution of 21.1 % FWHM at 140 keV, and a sensitivity of 481 and 73 cps/MBq when using the single- and double-layer collimators, respectively.