High baseline perivascular space volume in basal ganglia is associated with attention and executive function decline in Parkinson's disease.

BACKGROUND: Pathologic perivascular spaces (PVS), the fluid-filled compartments surrounding brain vasculature, may underlie cognitive decline in Parkinson's disease (PD). However, whether this impacts specific cognitive domains has not been investigated. OBJECTIVES: This study examined the relationship of PVS volume at baseline with domain-specific and global cognitive change over 2 years in PD individuals. METHODS: A total of 39 individuals with PD underwent 3T T1w magnetic resonance imaging to determine PVS volume fraction (PVS volume normalized to total regional volume) within (i) centrum semiovale, (ii) prefrontal white matter (medial orbitofrontal, rostral middle frontal, and superior frontal), and (iii) basal ganglia. A neuropsychological battery included assessment of cognitive domains and global cognitive function at baseline and after 2 years. RESULTS: Higher basal ganglia PVS at baseline was associated with greater decline in attention, executive function, and global cognition scores. CONCLUSIONS: While previous reports have associated elevated PVS volume in the basal ganglia with decline in global cognition in PD, our findings show such decline may affect the attention and executive function domains.

Absolute values of regional ventilation-perfusion mismatch in patients with ARDS monitored by electrical impedance tomography and the role of dead space and shunt compensation.

BACKGROUND: Assessment of regional ventilation/perfusion (V'/Q) mismatch using electrical impedance tomography (EIT) represents a promising advancement for personalized management of the acute respiratory distress syndrome (ARDS). However, accuracy is still hindered by the need for invasive monitoring to calibrate ventilation and perfusion. Here, we propose a non-invasive correction that uses only EIT data and characterized patients with more pronounced compensation of V'/Q mismatch. METHODS: We enrolled twenty-one ARDS patients on controlled mechanical ventilation. Cardiac output was measured invasively, and ventilation and perfusion were assessed by EIT. Relative V'/Q maps by EIT were calibrated to absolute values using the minute ventilation to invasive cardiac output (MV/CO) ratio (V'/Q-ABS), left unadjusted (V'/Q-REL), or corrected by MV/CO ratio derived from EIT data (V'/Q-CORR). The ratio between ventilation to dependent regions and perfusion reaching shunted units ( V D ' /QSHUNT) was calculated as an index of more effective hypoxic pulmonary vasoconstriction. The ratio between perfusion to non-dependent regions and ventilation to dead space units (QND/ V DS ' ) was calculated as an index of hypocapnic pneumoconstriction. RESULTS: Our calibration factor correlated with invasive MV/CO (r = 0.65, p < 0.001), showed good accuracy and no apparent bias. Compared to V'/Q-ABS, V'/Q-REL maps overestimated ventilation (p = 0.013) and perfusion (p = 0.002) to low V'/Q units and underestimated ventilation (p = 0.011) and perfusion (p = 0.008) to high V'/Q units. The heterogeneity of ventilation and perfusion reaching different V'/Q compartments was underestimated. V'/Q-CORR maps eliminated all these differences with V'/Q-ABS (p > 0.05). Higher V D ' / Q SHUNT correlated with higher PaO2/FiO2 (r = 0.49, p = 0.025) and lower shunt fraction (ρ = - 0.59, p = 0.005). Higher Q ND / V DS ' correlated with lower PEEP (ρ = - 0.62, p = 0.003) and plateau pressure (ρ = - 0.59, p = 0.005). Lower values of both indexes were associated with less ventilator-free days (p = 0.05 and p = 0.03, respectively). CONCLUSIONS: Regional V'/Q maps calibrated with a non-invasive EIT-only method closely approximate the ones obtained with invasive monitoring. Higher efficiency of shunt compensation improves oxygenation while compensation of dead space is less needed at lower airway pressure. Patients with more effective compensation mechanisms could have better outcomes.

Impacts of wildfire-season air quality on park and playground visitation in the Northwest United States.

A significant cost of wildfires is the exposure of local and regional populations to air pollution from smoke, which can travel hundreds of miles from the source fire and is associated with significant negative health consequences. Wildfires are increasing in frequency and intensity in the United States, driven by historic fire management approaches and global climate change. These influences will take many decades or longer to reverse, so the main opportunities for mitigating health effects involve minimizing human exposure through changes in behavior or infrastructure. One key recommendation for reducing pollution exposures during wildfire smoke events is to limit time and physical activity outdoors, but there is limited evidence on the extent to which people make this change. We estimate how use of parks and playgrounds changes with air quality during wildfire season in the northwest United States. We find small reductions in park and playground visits on moderately polluted days, and large reductions, to 50-60% of baseline visits, when pollution levels are high. Disaggregating results by neighborhood characteristics, we find a significantly greater behavioral response to moderate levels of air pollution in neighborhoods with higher socio-economic status, although responses to high levels of pollution are similar across neighborhood types.

Extremophiles in Space Exploration.

In the era of deep space exploration, extremophile research represents a key area of research w.r.t space survival. This review thus delves into the intriguing realm of 'Space and Astro Microbiology', providing insights into microbial survival, resilience, and behavioral adaptations in space-like environments. This discussion encompasses the modified behavior of extremophilic microorganisms, influencing virulence, stress resistance, and gene expression. It then shifts to recent studies on the International Space Station and simulated microgravity, revealing microbial responses that impact drug susceptibility, antibiotic resistance, and its commercial implications. The review then transitions into Astro microbiology, exploring the possibilities of interplanetary transit, lithopanspermia, and terraforming. Debates on life's origin and recent Martian meteorite discoveries are noted. We also discuss Proactive Inoculation Protocols for selecting adaptable microorganisms as terraforming pioneers. The discussion concludes with a note on microbes' role as bioengineers in bioregenerative life support systems, in recycling organic waste for sustainable space travel; and in promoting optimal plant growth to prepare Martian and lunar basalt. This piece emphasizes the transformative impact of microbes on the future of space exploration.

Short-term changes in chest CT images among individuals at low altitude after entering high-altitude environments.

Objective: To investigate the short-term changes in chest CT images of low-altitude populations after entering a high-altitude environment. Methods: Chest CT images of 3,587 people from low-altitude areas were obtained within one month of entering a high-altitude environment. Abnormal CT features and clinical symptoms were analyzed. Results: Besides acute high-altitude pulmonary edema, the incidence of soft tissue space pneumatosis was significantly higher than that in low-altitude areas. Pneumatosis was observed in the mediastinum, cervical muscle space, abdominal cavity, and spinal cord epidural space, especially the mediastinum. Conclusion: In addition to acute high-altitude pulmonary edema, spontaneous mediastinal emphysema often occurs when individuals in low-altitude areas adapt to the high-altitude environment of cold, low-pressure, and hypoxia. When the gas escapes to the abdominal cavity, it is easy to be misdiagnosed as gastrointestinal perforation. It is also not uncommon for gas accumulation to escape into the epidural space of the spinal cord. The phenomenon of gas diffusion into distant tissue space and the mechanism of gas escape needs to be further studied.

Quality space computations for consciousness.

The quality space hypothesis about conscious experience proposes that conscious sensory states are experienced in relation to other possible sensory states. For instance, the colour red is experienced as being more like orange, and less like green or blue. Recent empirical findings suggest that subjective similarity space can be explained in terms of similarities in neural activation patterns. Here, we consider how localist, workspace, and higher-order theories of consciousness can accommodate claims about the qualitative character of experience and functionally support a quality space. We review existing empirical evidence for each of these positions, and highlight novel experimental tools, such as altering local activation spaces via brain stimulation or behavioural training, that can distinguish these accounts.

The influence of travel time on perceived traveled distance varies by spatiotemporal scale.

The influence of travel time on perceived traveled distance has often been studied, but the results are inconsistent regarding the relationship between the two magnitudes. We argue that this is due to differences in the lengths of investigated travel distances and hypothesize that the influence of travel time differs for rather short compared to rather long traveled distances. We tested this hypothesis in a virtual environment presented on a desktop as well as through a head-mounted display. Our results show that, for longer distances, more travel time leads to longer perceived distance, while we do not find an influence of travel time on shorter distances. The presentation through an HMD vs. desktop only influenced distance judgments in the short distance condition. These results are in line with the idea that the influence of travel time varies by the length of the traveled distance, and provide insights on the question of how distance perception in path integration studies is affected by travel time, thereby resolving inconsistencies reported in previous studies.

Simulation-based optimization and experimental comparison of intracranial T2-weighted DANTE-SPACE vessel wall imaging at 3T and 7T.

PURPOSE: T2-weighted DANTE-SPACE (Delay Alternating with Nutation for Tailored Excitation - Sampling Perfection with Application optimized Contrasts using different flip angle Evolution) sequences facilitate non-invasive intracranial vessel wall imaging at 7T through simultaneous suppression of blood and CSF. However, the achieved vessel wall delineation depends closely on the selected sequence parameters, and little information is available about the performance of the sequence using more widely available 3T MRI. Therefore, in this paper a comprehensive DANTE-SPACE simulation framework is used for the optimization and quantitative comparison of T2-weighted DANTE-SPACE at both 7T and 3T. METHODS: Simulations are used to propose optimized sequence parameters at both 3T and 7T. At 7T, an additional protocol which uses a parallel transmission (pTx) shim during the DANTE preparation for improved suppression of inflowing blood is also proposed. Data at both field strengths using optimized and literature protocols are acquired and quantitatively compared in six healthy volunteers. RESULTS: At 7T, more vessel wall signal can be retained while still achieving sufficient CSF suppression by using fewer DANTE pulses than described in previous implementations. The use of a pTx shim during DANTE at 7T provides a modest further improvement to the inner vessel wall delineation. At 3T, aggressive DANTE preparation is required to achieve CSF suppression, resulting in reduced vessel wall signal. As a result, the achievable vessel wall definition at 3T is around half that of 7T. CONCLUSION: Simulation-based optimization of DANTE parameters facilitates improved T2-weighted DANTE-SPACE contrasts at 7T. The improved vessel definition of T2-weighted DANTE-SPACE at 7T makes DANTE preparation more suitable for T2-weighted VWI at 7T than at 3T.

Relationship between epidural catheter migration beneath the skin and subcutaneous fat thickness assessed using postoperative CT imaging: a retrospective cross-sectional study.

PURPOSE: The causes of epidural catheter migration beneath the skin have not been previously investigated. We hypothesized that greater subcutaneous fat thickness might be associated with increased catheter migration beneath the skin. METHODS: We conducted a retrospective cross-sectional study of patients who had undergone combined general and epidural anesthesia, selecting individuals who received thoracic and abdominal CT scans within the first 5 postoperative days. Needle depth was defined as the distance from the needle tip to the skin surface when the anesthesiologist determined that the needle tip had reached the epidural space. We measured the length of the epidural catheter from the skin surface to the epidural space (catheter length), and subcutaneous fat thickness (fat thickness) using CT imaging. Migration distance was calculated by subtracting needle depth from catheter length. RESULTS: We analyzed 127 patients (72 males), all undergoing epidural catheter insertion in the left lateral decubitus position via a paramedian approach. The median age of the patients was 71 years. Epidural catheters were postoperatively found to substantially curve beneath the skin. Regression analysis revealed no significant influence of fat thickness on catheter length (regression coefficient 0.10, 95% confidence interval [CI]: - 0.17, 0.38). However, it indicated a positive correlation between fat thickness and needle depth (regression coefficient 0.50, 95% CI: 0.30, 0.70), and a negative correlation between fat thickness and migration distance (regression coefficient - 0.40, 95% CI: - 0.65, - 0.14). CONCLUSION: We found a negative correlation between epidural catheter migration beneath the skin and subcutaneous fat thickness. Anesthesiologists should be aware of the possibility of substantial subcutaneous curving of the catheter, especially in patients with scant subcutaneous fat.

Control of anterior anchorage with miniscrews and sliding mechanics in an adolescent with missing second premolars: A clinical report with biomechanical validation.

Congenital missing second premolars in growing patients should be accurately evaluated in order to establish a suitable treatment plan. Concerning the decision of whether to close or maintain spaces in the dental arches, it shall also be based on biomechanical aspects and the aesthetic traits of individual patients. Accordingly, the option of closing tooth spaces requires an adequate application of biomechanical principles aimed at avoiding detrimental effects on dental arches and facial profile. An effective use of titanium miniscrews for immediate loading, associated with efficient sliding mechanics, can represent an elective way to successfully treat such cases. Herein, the objective is to describe the procedure and underscore the advantages of the mentioned approach by presenting a clinical case along with long-term follow-up.

Rare case of giant ischiorectal leiomyosarcoma.

INTRODUCTION: Leiomyosarcoma is a rare type of soft tissue sarcoma especially giant ones (size >5 cm). It is usually arises from the uterus and retroperitoneum. Ischiorectal space is not a common site for primary leomyosarcoma. There are only few case reports about Ischiorectal leiomyosarcoma. PRESENTATION OF CASE: We present a case of 25 yrs. old female patient, who presented with a swelling on left buttock. It measures 9 by 9.5 by 18 cm on MRI. Complete tumor excision done and immunohistochemistry tests confirmed the diagnosis of leiomyosarcoma. DISCUSSION: Due to its rarity, unusual site and large size leiomyosarcoma poses a great challenge for a surgeon both to diagnose and manage it. Early diagnosis and management improves prognosis and decreases recurrence rate because sarcomas have high recurrence rate. It is highly recommended to have multidisciplinary approach. CONCLUSION: The case report highlights on both diagnostic and therapeutic challenges associated with giant leiomyosarcoma. There are no strict guidelines to follow when managing this type of cases but rather approach has to be individualized. Since there are only few case reports on this specific pathology we advocate for surgeons to share their experience on similar cases.

Preoperative Contrast-Enhanced CT-Based Deep Learning Radiomics Model for Distinguishing Retroperitoneal Lipomas and Well­Differentiated Liposarcomas.

RATIONALE AND OBJECTIVES: To assess the efficacy of a preoperative contrast-enhanced CT (CECT)-based deep learning radiomics nomogram (DLRN) for predicting murine double minute 2 (MDM2) gene amplification as a means of distinguishing between retroperitoneal well-differentiated liposarcomas (WDLPS) and lipomas. METHODS: This retrospective multi-center study included 167 patients (training/external test cohort, 104/63) with MDM2-positive WDLPS or MDM2-negative lipomas. Clinical data and CECT features were independently measured and analyzed by two radiologists. A clinico-radiological model, radiomics signature (RS), deep learning and radiomics signature (DLRS), and a DLRN incorporating radiomics and deep learning features were developed to differentiate between WDLPS and lipoma. The model utility was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, calibration curve, and decision curve analysis (DCA). RESULTS: The DLRN showed good performance for distinguishing retroperitoneal lipomas and WDLPS in the training (AUC, 0.981; accuracy, 0.933) and external validation group (AUC, 0.861; accuracy, 0.810). The DeLong test revealed the DLRN was noticeably better than clinico-radiological and RS models (training: 0.981 vs. 0.890 vs. 0.751; validation: 0.861 vs. 0.724 vs. 0.700; both P < 0.05); however, no discernible difference in performance was seen between the DLRN and DLRS (training: 0.981 vs. 0.969; validation: 0.861 vs. 0.837; both P > 0.05). The calibration curve analysis and DCA demonstrated that the nomogram exhibited good calibration and offered substantial clinical advantages. CONCLUSION: The DLRN exhibited strong predictive capability in predicting WDLPS and retroperitoneal lipomas preoperatively, making it a promising imaging biomarker that can facilitate personalized management and precision medicine.

Urban greenspace types and climate factors jointly drive the microbial community structure and co-occurrence network.

The benefits of urban green space are socially widely recognized as a direct link between plant-microbe interactions and the maintenance of biodiversity, community stability, and ecosystem functioning. Nevertheless, there is a lack of knowledge about the factors influencing microbial communities in urban green spaces, especially those related to phyllosphere epiphytes and stem epiphytes. In this study, we analyzed the microbial community assembly in leaf and stem bark samples collected from Square, Road, Campus, and Park. Illumina sequecing of 16S amplicons was performed to characterize microbial diversity and composition. The α-diversity was significantly higher in the bark epiphytic community, compared to the phyllosphere. Moreover, urban greenspaces'type altered the way communities gathered. The main soil and air properties factors of the urban greenhouse (e.g. soil temperature, atmospheric moisture, air temperature) were shaping the characteristics of bacterial communities on the leaf surface and bark epiphytic. In addition, in the co-occurrence network analysis, keystone taxa were not mostly observed in abundant species, which may be necessary to maintain ecosystem functions. Finally, our findings provide a deeper understanding of the ecological dynamics and microbial interactions within plant phyllosphere and stem epiphytes microbiomes.

Fire protection priorities in the oak forests of Iran with an emphasis on vertebrate habitat preservation.

This study examines the impact of fire incidents on wildlife and habitats in the western oak forests of Iran (Zagros region). These forests are globally recognized for their exceptional biodiversity but are frequently threatened by wildfires. To achieve this, the study uses the space-time scan statistics permutation (STSSP) model to identify areas with a higher frequency of fires. The study also analyzes the effects of fires on the Zagros forests from 2000 to 2021 using remote-sensing MODIS data. Also, to understand the elements at risk of fire, burned areas were assessed based on the richness of vertebrate species, determined by the distribution of 88 vertebrate species. The results show that the annual fire rate in the Zagros forests is 76.2 (fire occurrences per year), calculated using the Poisson distribution. Findings show the highest fire rates are found in the northwest and a part of the south of the Zagros. The northwest of the Zagros also has the largest number of single fires and clusters, indicating a wide spatial distribution of fire in these regions. On the other side, it was unexpectedly found that these regions have the richest number of species and higher habitat value. The results demonstrate a significant correlation between the value of the habitat and the extent of burned areas (p < 0.05). The study also reveals that the greatest impact of fires is on small vertebrates. The overlap of frequent fire spots with the richest regions of Zagros oak forests in terms of vertebrate diversity emphasizes the need for strategic forest risk reduction planning, especially in these priority zones.

DrugMetric: quantitative drug-likeness scoring based on chemical space distance.

The process of drug discovery is widely known to be lengthy and resource-intensive. Artificial Intelligence approaches bring hope for accelerating the identification of molecules with the necessary properties for drug development. Drug-likeness assessment is crucial for the virtual screening of candidate drugs. However, traditional methods like Quantitative Estimation of Drug-likeness (QED) struggle to distinguish between drug and non-drug molecules accurately. Additionally, some deep learning-based binary classification models heavily rely on selecting training negative sets. To address these challenges, we introduce a novel unsupervised learning framework called DrugMetric, an innovative framework for quantitatively assessing drug-likeness based on the chemical space distance. DrugMetric blends the powerful learning ability of variational autoencoders with the discriminative ability of the Gaussian Mixture Model. This synergy enables DrugMetric to identify significant differences in drug-likeness across different datasets effectively. Moreover, DrugMetric incorporates principles of ensemble learning to enhance its predictive capabilities. Upon testing over a variety of tasks and datasets, DrugMetric consistently showcases superior scoring and classification performance. It excels in quantifying drug-likeness and accurately distinguishing candidate drugs from non-drugs, surpassing traditional methods including QED. This work highlights DrugMetric as a practical tool for drug-likeness scoring, facilitating the acceleration of virtual drug screening, and has potential applications in other biochemical fields.

Urban health advantage and penalty in aging populations: a comparative study across major megacities in China.

Background: Urban living is linked to better health outcomes due to a combination of enhanced access to healthcare, transportation, and human development opportunities. However, spatial inequalities lead to disparities, resulting in urban health advantages and penalties. Understanding the relationship between health and urban development is needed to generate empirical evidence in promoting healthy aging populations. This study provides a comparative analysis using epidemiological evidence across diverse major Chinese cities, examining how their unique urban development trajectories over time have impacted the health of their aging residents. Methods: We tracked changes in air pollution (NO2, PM2.5, O3), green space (measured by NDVI), road infrastructure (ring road areas), and nighttime lighting over 20 years in six major cities in China. We followed a longitudinal cohort of 4992 elderly participants (average age 87.8 years) over 16,824 person-years. We employed Cox proportional hazard regression to assess longevity, assessing 14 variables, including age, sex, ethnicity, marital status, residence, household income, occupation, education, smoking, alcohol consumption, exercise, and points of interest (POI) count of medicine-related facilities, sports, and leisure service-related places, and scenic spots within a 5 km-radius buffer. Findings: Geographic proximity to points of interest significantly improves survival. Elderly living in proximity of the POI-rich areas had a 34.6%-35.6% lower mortality risk compared to those in POI-poor areas, for the highest compared to the lowest quartile. However, POI-rich areas had higher air pollution levels, including PM2.5 and NO2, which was associated with a 21% and 10% increase in mortality risk for increase of 10 µg/m3, respectively. The benefits of urban living had higher effect estimates in monocentric cities, with clearly defined central areas, compared to polycentric layouts, with multiple satellite city centers. Interpretation: Spatial inequalities create urban health advantages for some and penalties for others. Proximity to public facilities and economic activities is associated with health benefits, and may counterbalance the negative health impacts of lower green space and higher air pollution. Our empirical evidence show optimal health gains for age-friendly urban environments come from a balance of infrastructure, points of interest, green spaces, and low air pollution. Funding: Natural Science Foundation of Beijing (IS23105), National Natural Science Foundation of China (82250610230, 72061137004), World Health Organization (2024/1463606-0), Research Fund Vanke School of Public Health Tsinghua University (2024JC002), Beijing TaiKang YiCai Public Welfare Foundation, National Key R&D Program of China (2018YFC2000400).

Real space method for HAADF image simulation.

A new real space HAADF simulation method was described in detail and a Real Space- STEM software was developed based on the new simulation method. The algorithm of the real space method can quickly calculate and simulate the microstructure images of complex crystals. The Real Space-STEM software developed in this paper has the functions of HRTEM and HAADF image simulation based on the real space method. By using this software to simulate high-resolution images of representative crystal materials from each crystal system, the HAADF images are both accurate and efficient. The effect of STEM parameters on HAADF imaging has been discussed using simulation results.

Optical Thin Films in Space Environment: Investigation of Proton Irradiation Damage.

The present work reports a systematic study of the potential degradation of metals and dielectric thin films in different space environments. The mono- and bilayers selected are made of materials commonly used for the realization of optical components, such as reflective mirrors or building blocks of interferential filters. More than 400 samples were fabricated and irradiated with protons at different energies on ground-based facilities. The fluences were selected as a result of simulations of the doses delivered within a long-term space mission considering different orbits (Sun close, Jovian, and Geostationary orbits). In order to stress the samples at different depths and layer interfaces, experiments were carried out with a range of proton energies within 1 and 10 MeV values. An estimate of a safe maximum fluence has been provided for each type of sample at each energy. The damage mechanism, when present, has been investigated with different optical and structural techniques.

Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction.

OBJECTIVES: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy. MATERIALS AND METHODS: A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation. RESULTS: Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR. CONCLUSION: DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy. CLINICAL RELEVANCE STATEMENT: This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.