Event-free survival by residual cancer burden with pembrolizumab in early-stage TNBC: exploratory analysis from KEYNOTE-522.

BACKGROUND: KEYNOTE-522 demonstrated statistically significant improvements in pathological complete response (pCR) with neoadjuvant pembrolizumab plus chemotherapy and event-free survival (EFS) with neoadjuvant pembrolizumab plus chemotherapy followed by adjuvant pembrolizumab in patients with high-risk, early-stage triple-negative breast cancer (TNBC). Prior studies have shown the prognostic value of the residual cancer burden (RCB) index to quantify the extent of residual disease after neoadjuvant chemotherapy. In this preplanned exploratory analysis, we assessed RCB distribution and EFS within RCB categories by treatment group. PATIENTS AND METHODS: A total of 1174 patients with stage T1c/N1-2 or T2-4/N0-2 TNBC were randomized 2 : 1 to pembrolizumab 200 mg or placebo every 3 weeks given with four cycles of paclitaxel + carboplatin, followed by four cycles of doxorubicin or epirubicin + cyclophosphamide. After surgery, patients received pembrolizumab or placebo for nine cycles or until recurrence or unacceptable toxicity. Primary endpoints are pCR and EFS. RCB is a prespecified exploratory endpoint. The association between EFS and RCB was assessed using a Cox regression model. RESULTS: Pembrolizumab shifted patients into lower RCB categories across the entire spectrum compared with placebo. There were more patients in the pembrolizumab group with RCB-0 (pCR), and fewer patients in the pembrolizumab group with RCB-1, RCB-2, and RCB-3. The corresponding hazard ratios (95% confidence intervals) for EFS were 0.70 (0.38-1.31), 0.92 (0.39-2.20), 0.52 (0.32-0.82), and 1.24 (0.69-2.23). The most common first EFS events were distant recurrences, with fewer in the pembrolizumab group across all RCB categories. Among patients with RCB-0/1, more than half [21/38 (55.3%)] of all events were central nervous system recurrences, with 13/22 (59.1%) in the pembrolizumab group and 8/16 (50.0%) in the placebo group. CONCLUSIONS: Addition of pembrolizumab to chemotherapy resulted in fewer EFS events in the RCB-0, RCB-1, and RCB-2 categories, with the greatest benefit in RCB-2. These findings demonstrate that pembrolizumab not only increased pCR rates, but also improved EFS among most patients who do not have a pCR.

Prevalence of Salmonella spp. and Escherichia coli in the feces of free-roaming wildlife throughout South Korea.

Wildlife can carry pathogenic organisms, including viruses, bacteria, parasites, and fungi, which can spread to humans and cause mild to serious illnesses and even death. Spreading through animal feces, these pathogens significantly contributes to the global burden of human diseases. Therefore, the present study investigated the prevalence of zoonotic bacterial pathogens, such as Salmonella spp., Escherichia coli, and Shiga toxin-producing E. coli (STEC), in animal feces. Between September 2015 and August 2017, 699 wildlife fecal samples were collected from various agricultural production regions and mountainous areas in South Korea. Fecal samples were collected from wild mammals (85.26%, 596/699) and birds (14.73%, 103/699). Salmonella spp. and E. coli were present in 3% (21/699) and 45.63% (319/699) of the samples, respectively. Moreover, virulence genes stx1 and both stx1 and stx2 were detected in 13.30% (93/699) and 0.72% (5/699) of the samples, respectively. The 21 Salmonella spp. were detected in badgers (n = 5), leopard cats (n = 7), wild boars (n = 2), and magpies (n = 7); STEC was detected in roe deer, water deer, mice, and wild boars. Through phylogenetic and gene-network analyses, the Salmonella spp. isolates (n = 21 laboratory isolates, at least one isolate from each Salmonella-positive animal fecal sample, and n = 6 widely prevalent reference Salmonella serovars) were grouped into two major lineages: S. enterica subsp. enterica and S. enterica subsp. diarizonae. Similarly, 93 E. coli isolates belonged to stx1, including three major lineages (groups 1-3), and stx1 and stx2 detected groups. To the best of our knowledge, this is the first report of a wild leopard cat serving as a reservoir for Salmonella spp. in South Korea. The research findings can help manage the potential risk of wildlife contamination and improve precautionary measures to protect public health.

Trastuzumab deruxtecan in previously treated patients with HER2-positive metastatic breast cancer: updated survival results from a phase II trial (DESTINY-Breast01).

BACKGROUND: Primary analysis of the multicenter, open-label, single-arm, phase II DESTINY-Breast01 trial (median follow-up 11.1 months) demonstrated durable antitumor activity with trastuzumab deruxtecan (T-DXd) in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (mBC) previously treated with trastuzumab emtansine (T-DM1). We report updated cumulative survival outcomes with a median follow-up of 26.5 months (data cut-off 26 March 2021). PATIENTS AND METHODS: Patients with HER2-positive mBC resistant or refractory to T-DM1 received T-DXd 5.4 mg/kg intravenously every 3 weeks until disease progression, unacceptable adverse events, or withdrawal of consent. The primary endpoint was confirmed objective response rate (ORR) by independent central review (ICR). Secondary endpoints included overall survival (OS), duration of response (DoR), progression-free survival (PFS), and safety. RESULTS: The ORR by ICR was 62.0% [95% confidence interval (CI) 54.5% to 69.0%] in patients who received T-DXd 5.4 mg/kg every 3 weeks (n = 184). Median OS was 29.1 months (95% CI 24.6-36.1 months). Median PFS and DoR were 19.4 months (95% CI 14.1-25.0 months) and 18.2 months (95% CI 15.0 months-not evaluable), respectively. Drug-related treatment-emergent adverse events (TEAEs) were observed in 183 patients (99.5%), and 99 patients (53.8%) had one or more grade ≥3 TEAEs. Adjudicated drug-related interstitial lung disease/pneumonitis occurred in 15.8% of patients (n = 29), of which 2.7% (n = 5) were grade 5. CONCLUSIONS: These updated results provide further evidence of sustained antitumor activity of T-DXd with a consistent safety profile in heavily pretreated patients with HER2-positive mBC.

Geographic variation and trends in prevalence of obesity among US adolescents, 2016-2021.

OBJECTIVE: Recent updates of geographic variations, trends, and sociodemographic disparities in obesity prevalence among US adolescents are limited. The study aimed to fill those research gaps. STUDY DESIGN: Serial cross-sectional analysis of the US nationally representative study. METHODS: Data from six cycles of the National Survey of Children's Health (2016, 2017, 2018, 2019, 2020, and 2021) with information on physical health at the national and state level were used. A total of 107,274 adolescents aged 10-17 years old were included with sociodemographic data (age, sex, race/ethnicity, parental education level, and family income) and state of residence. Logistic regression models were used to estimate the odds ratios (ORs) associated with obesity across sociodemographic groups. In addition, ORs were calculated to compare obesity rates between the pandemic period (2020-2021) and the pre-pandemic period (2018-2019) overall and by sociodemographic subgroups. Survey analysis procedures were used to account for complex survey designs to derive representative estimates. RESULTS: From 2016 to 2021, obesity prevalence increased from 16.1% (95% confidence interval [CI], 14.9%-17.4%) to 17.6% (95% CI, 16.4%-18.9%) (P-trend = 0.04). The combined prevalence of obesity varies substantially by state, from 9.34% (95% CI, 6.96%-12.4%; Colorado) to 27.1% (95% CI, 23.1%-31.5%; Mississippi) for adolescents aged 10-13 years and ranged from 9.86% (95% CI, 7.63%-12.7%; Utah) to 22.4% (95% CI, 19.0%-26.1%; West Virginia) for adolescents aged 14-17 years. Except for subgroups male gender and parents with college degrees or above, the prevalence of obesity showed stable trends across sociodemographic subgroups. Compared to the pre-pandemic period, the multivariable-adjusted ORs of obesity were 1.18 (95% CI, 1.06-1.32) for male adolescents, 1.16 (95% CI, 1.04-1.28) for non-Hispanic White adolescents, 1.81 (95% CI, 1.15-2.84) for non-Hispanic Asian adolescents, 1.26 (95% CI, 1.05-1.52) for adolescents whose parents had a high school education, and 1.15 (95% CI, 1.0-1.33) for adolescents whose parents had a college degree or higher. CONCLUSIONS: The prevalence of obesity among US adolescents increased significantly between 2016 and 2021. The prevalence of obesity was relatively high in southern states. Those with low household income, low parental education, or being non-Hispanic Black or Hispanic were also more likely to be obese. Compared to the pre-pandemic period, several groups of adolescents increased their likelihood of obesity during the pandemic period.

Pan-Asian adapted ESMO Clinical Practice Guidelines for the diagnosis, staging and treatment of patients with metastatic breast cancer.

The most recent version of the European Society for Medical Oncology (ESMO) Clinical Practice Guidelines for the diagnosis, staging and treatment of patients with metastatic breast cancer (MBC) was published in 2021. A special, hybrid guidelines meeting was convened by ESMO and the Korean Society of Medical Oncology (KSMO) in collaboration with nine other Asian national oncology societies in May 2022 in order to adapt the ESMO 2021 guidelines to take into account the differences associated with the treatment of MBC in Asia. These guidelines represent the consensus opinions reached by a panel of Asian experts in the treatment of patients with MBC representing the oncological societies of China (CSCO), India (ISMPO), Indonesia (ISHMO), Japan (JSMO), Korea (KSMO), Malaysia (MOS), the Philippines (PSMO), Singapore (SSO), Taiwan (TOS) and Thailand (TSCO). The voting was based on the best available scientific evidence and was independent of drug access or practice restrictions in the different Asian countries. The latter were discussed when appropriate. The aim of these guidelines is to provide guidance for the harmonisation of the management of patients with MBC across the different regions of Asia, drawing from data provided by global and Asian trials whilst at the same time integrating the differences in genetics, demographics and scientific evidence, together with restricted access to certain therapeutic strategies.

Hydrogen production from hazardous petroleum sludge gasification over nickel-loaded porous ZSM-5 and Al2O3 catalysts under air condition.

In this study, the potential of petroleum sludge (PS) for hydrogen production via the gasification process was evaluated. For this purpose, nickel (Ni)-loaded ZSM-5 and γ-Al2O3 (Ni-ZS and Ni-Al) catalysts were prepared and employed for PS gasification in air condition. The effects of different supports, Ni loading content, and reaction temperatures on the production of hydrogen-rich syngas along with the stability and reusability of the best catalyst were investigated. Applying 5%Ni-ZS obtained more gas yield (68.09 wt%) and hydrogen selectivity (25.04 vol%) compared to those obtained by 5%Ni-Al mostly owing to weak metal-support interactions which led to the dominance of well-dispersed metallic Ni. At various Ni loading percentages, 10%Ni-ZS showed the highest catalytic efficiency, which increased both gas yield (70.92 wt%) and hydrogen selectivity (30.74 vol%). However, excessive Ni content (especially 20%) significantly reduced the gas yield and hydrogen selectivity because of limited accessibility of support's active sites, poor dispersion of Ni, and inappropriate acidity. Increasing the temperature promoted the gas yield and produced hydrogen, where the highest gas yield (73.18 wt%) and hydrogen selectivity (33.15 vol%) were obtained at 850 °C due to the endothermic nature of gasification reactions. The 10%Ni-ZS catalyst showed proper stability during three consecutive experiments at 850 °C. The spent catalyst was successfully regenerated without a significant reduction in activity or selectivity.

Catalytic ozonation of methylethylketone over porous Mn-Cu/HZSM-5.

The catalytic ozonation of methylethylketone (MEK) was performed at the room temperature (25 °C) using the synthesized Mn and Cu-loaded zeolite (ZSM-5, SiO2/Al2O3 = 80) catalysts. The ZSM-5 zeolite was used as a porous support material due to the large surface area and high capacity for adsorption of volatile organic compounds. Since Mn and Cu-loaded zeolite catalysts were effective for the catalytic ozonation of VOCs such as MEK, according to the loaded concentration of Mn and Cu, there are four types of metal loaded ZSM5 catalysts synthesized [5 wt% Mn/ZSM-5, 5 wt% Cu/ZSM-5, 5 wt% Mn-1 wt% Cu/ZSM-5 (5Mn1CuZSM), and 5 wt% Cu-1 wt% Mn/ZSM-5]. The catalytic efficiency for the removal of MEK and ozonation using the different catalysts was also studied. Based on various experimental analysis processes, the characteristics of the synthesized catalysts were explored and the removal efficiencies of MEK and O3 together with the COx concentration generated from the destruction of MEK and O3 were explored. The results for the decomposition of MEK and O3 at the room temperature indicated that the Mn dominant ZSM-5 catalysts showed better efficiency for the conversion of MEK and O3. The 5 wt% Mn/ZSM-5 outweighed the rest of them for the removal of MEK while the 5Mn1CuZSM showed the best catalytic reactivity for the conversion of O3 and the CO2 selectivity. It was ascertained that during the reaction time of catalyst and reactants of 120 min the Mn dominantly deposited bimetallic catalyst, 5Mn1CuZSM, was determined as the most effective for the removal of MEK and O3 due to the high capability of production of Mn3+ species and more available adsorbed oxygen sites compared to the other catalysts. Finally, the durability measurement for the 5Mn1CuZSM catalyst was performed together with the produced CO and CO2 concentration for 420 min.

Association between obsessive-compulsive disorder and the risk of schizophrenia using the Korean National Health Insurance Service-National Sample Cohort: a retrospective cohort study.

AIMS: Obsessive-compulsive disorder (OCD) and schizophrenia are often reported as co-morbid conditions. However, the evidence of an association between OCD and the risk of schizophrenia is limited. This study investigated the risk of schizophrenia in patients newly diagnosed with OCD using a nationally representative sample cohort in South Korea. METHODS: Data were obtained from the 2002-2013 Korean National Health Insurance Service-National Sample Cohort of the National Health Insurance Service. Using propensity score matching, 2509 patients with OCD and a control group of 7527 patients were included in the analysis. Chi-squared tests were used to investigate and compare the general characteristics of the study population. The risk of schizophrenia was analysed using the Cox proportional hazard model. RESULTS: The incidence rate was 45.79/10 000 person-year for patients with OCD and 4.19/10 000 person-year for patients without OCD. Patients with OCD had a higher risk of schizophrenia compared to the control group after adjusting for covariates (hazard ratio = 10.46, 95% confidence interval = 6.07-18.00). CONCLUSIONS: This study identified an association between the diagnosis of OCD and the risk of schizophrenia in a South Korean national representative cohort. Further research using a prospective design to clarify the causality of OCD in schizophrenia in a controlled environment should be conducted to validate these findings.

Recurrent neural networks for dynamical systems: Applications to ordinary differential equations, collective motion, and hydrological modeling.

Classical methods of solving spatiotemporal dynamical systems include statistical approaches such as autoregressive integrated moving average, which assume linear and stationary relationships between systems' previous outputs. Development and implementation of linear methods are relatively simple, but they often do not capture non-linear relationships in the data. Thus, artificial neural networks (ANNs) are receiving attention from researchers in analyzing and forecasting dynamical systems. Recurrent neural networks (RNNs), derived from feed-forward ANNs, use internal memory to process variable-length sequences of inputs. This allows RNNs to be applicable for finding solutions for a vast variety of problems in spatiotemporal dynamical systems. Thus, in this paper, we utilize RNNs to treat some specific issues associated with dynamical systems. Specifically, we analyze the performance of RNNs applied to three tasks: reconstruction of correct Lorenz solutions for a system with a formulation error, reconstruction of corrupted collective motion trajectories, and forecasting of streamflow time series possessing spikes, representing three fields, namely, ordinary differential equations, collective motion, and hydrological modeling, respectively. We train and test RNNs uniquely in each task to demonstrate the broad applicability of RNNs in the reconstruction and forecasting the dynamics of dynamical systems.

Sewage sludge steam gasification over bimetallic mesoporous Al-MCM48 catalysts for efficient hydrogen generation.

This study explored the potential of steam gasification of sewage sludge over different temperatures (non-catalytic) and bimetallic (Ni-Fe and Ni-Co) mesoporous Al-MCM48 (3-5% Al basis). The higher temperature (800 °C) resulted in higher gas yield (36.74 wt%) and syngas (H2 and CO) selectivity (35.30 vol% and 11.66 vol%). Moreover, catalytic approach displayed that the Al-MCM48 was effective support because the incorporation of nickel increased the efficiency of gasification reactions compared to HZSM-5 (30). It mainly comes from the presence of mesopores and higher surface area (710.05 m2/g) providing more reaction sites and higher stability (less coke formation). Furthermore, the addition of promoters such as Co and Fe allowed the formation of Ni-Fe and Ni-Co alloys, resulting in even higher gas yield and overall H2 and CO selectivity due to the promotion of related reactions such as tar cracking, Boudouard, water gas shift and reforming and so on. Ni-Co alloy catalyst (10% Ni-5% Co/Al-MCM48) resulted in the highest H2 (∼52 vol%) selectivity due to the enhanced Ni dispersion and synergy effect between Ni and Co. Moreover, the application of bi-metal alloy on Al-MCM48 showed no coke formation and significantly reduced CO2 and hydrocarbon selectivity in the product gas. Overall, this study presented a promising solution for sewage sludge disposal in terms of clean H2 generation, reduction in CO2 and higher stability of metal based catalysts at the same time.

A New Approach to Quantify and Grade Radiation Dermatitis Using Deep-Learning Segmentation in Skin Photographs.

AIMS: Objective evaluation of radiation dermatitis is important for analysing the correlation between the severity of radiation dermatitis and dose distribution in clinical practice and for reliable reporting in clinical trials. We developed a novel radiation dermatitis segmentation system based on convolutional neural networks (CNNs) to consistently evaluate radiation dermatitis. MATERIALS AND METHODS: The radiation dermatitis segmentation system is designed to segment the radiation dermatitis occurrence area using skin photographs and skin-dose distribution. A CNN architecture with a dilated convolution layer and skip connection was designed to estimate the radiation dermatitis area. Seventy-three skin photographs obtained from patients undergoing radiotherapy were collected for training and testing. The ground truth of radiation dermatitis segmentation is manually delineated from the skin photograph by an experienced radiation oncologist and medical physicist. We converted the skin photographs to RGB (red-green-blue) and CIELAB (lightness (L∗), red-green (a∗) and blue-yellow (b∗)) colour information and trained the network to segment faint and severe radiation dermatitis using three different input combinations: RGB, RGB + CIELAB (RGBLAB) and RGB + CIELAB + skin-dose distribution (RGBLAB_D). The proposed system was evaluated using the Dice similarity coefficient (DSC), sensitivity, specificity and normalised Matthews correlation coefficient (nMCC). A paired t-test was used to compare the results of different segmentation performances. RESULTS: Optimal data composition was observed in the network trained for radiation dermatitis segmentation using skin photographs and skin-dose distribution. The average DSC, sensitivity, specificity and nMCC values of RGBLAB_D were 0.62, 0.61, 0.91 and 0.77, respectively, in faint radiation dermatitis, and 0.69, 0.78, 0.96 and 0.83, respectively, in severe radiation dermatitis. CONCLUSION: Our study showed that CNN-based radiation dermatitis segmentation in skin photographs of patients undergoing radiotherapy can describe radiation dermatitis severity and pattern. Our study could aid in objectifying the radiation dermatitis grading and analysing the reliable correlation between dosimetric factors and the morphology of radiation dermatitis.

Search for 70 µeV Dark Photon Dark Matter with a Dielectrically Loaded Multiwavelength Microwave Cavity.

Microwave cavities have been deployed to search for bosonic dark matter candidates with masses of a few µeV. However, the sensitivity of these cavity detectors is limited by their volume, and the traditionally employed half-wavelength cavities suffer from a significant volume reduction at higher masses. Axion dark matter experiment (ADMX)-Orpheus mitigates this issue by operating a tunable, dielectrically loaded cavity at a higher-order mode, which allows the detection volume to remain large. The ADMX-Orpheus inaugural run excludes dark photon dark matter with kinetic mixing angle χ>10^{-13} between 65.5 µeV (15.8 GHz) and 69.3 µeV (16.8 GHz), marking the highest-frequency tunable microwave cavity dark matter search to date.

Electro-optic sampling based characterization of broad-band high efficiency THz-FEL.

Extremely high beam-to-radiation energy conversion efficiencies can be obtained in a THz FEL using a strongly tapered helical undulator at the zero-slippage resonant condition, where a circular waveguide is used to match the radiation group velocity to the electron beam longitudinal velocity. In this paper we report on the first electro-optic sampling (EOS) based measurements of the broadband THz FEL radiation pulses emitted in this regime. The THz field waveforms are reconstructed in the spatial and temporal domains using multi-shot and single-shot EOS schemes respectively. The measurements are performed varying the input electron beam energy in the undulator providing insights on the complex dynamics in a waveguide FEL.

A sustained high-temperature fusion plasma regime facilitated by fast ions.

Nuclear fusion is one of the most attractive alternatives to carbon-dependent energy sources1. Harnessing energy from nuclear fusion in a large reactor scale, however, still presents many scientific challenges despite the many years of research and steady advances in magnetic confinement approaches. State-of-the-art magnetic fusion devices cannot yet achieve a sustainable fusion performance, which requires a high temperature above 100 million kelvin and sufficient control of instabilities to ensure steady-state operation on the order of tens of seconds2,3. Here we report experiments at the Korea Superconducting Tokamak Advanced Research4 device producing a plasma fusion regime that satisfies most of the above requirements: thanks to abundant fast ions stabilizing the core plasma turbulence, we generate plasmas at a temperature of 100 million kelvin lasting up to 20 seconds without plasma edge instabilities or impurity accumulation. A low plasma density combined with a moderate input power for operation is key to establishing this regime by preserving a high fraction of fast ions. This regime is rarely subject to disruption and can be sustained reliably even without a sophisticated control, and thus represents a promising path towards commercial fusion reactors.

Regional and annual patterns in respiratory virus co-infection etiologies and antibiotic prescriptions for pediatric mycoplasma pneumoniae pneumonia.

OBJECTIVE: Mycoplasma pneumoniae (M. pneumoniae) pneumonia is the second-most common cause of community-acquired pneumonia (CAP). This study aimed at investigating into the prevalence of macrolide-resistant M. pneumoniae (MRMP) with respiratory virus co-infection and the antibiotic prescriptions in children with CAP in four provinces in Korea, and to assess the variations in the findings across regions and throughout the year. PATIENTS AND METHODS: This prospective study was conducted in 29 hospitals in Korea between July 2018 and June 2020. Among the enrolled 1,063 children with CAP, all 451 patients with M. pneumoniae underwent PCR assays of M. pneumoniae and respiratory viruses, and the presence of point mutations of residues 2063 and 2064 was evaluated. RESULTS: Gwangju-Honam (88.6%) showed the highest prevalence of MRMP pneumonia, while Daejeon-Chungcheong (71.3%) showed the lowest, although the differences in prevalence were not significant (p=0.074). Co-infection of M. pneumoniae pneumonia and respiratory virus was observed in 206 patients (45.4%), and rhinovirus co-infection (101 children; 22.2%) was the most frequent. The prevalence of MRMP pneumonia with respiratory virus co-infection and the antibiotic prescriptions differed significantly among the four provinces (p < 0.05). The monthly rate of MRMP pneumonia cases among all cases of M. pneumoniae pneumonia and tetracycline or quinolone prescriptions did not differ significantly among the four regions (trend p > 0.05) during the study period. CONCLUSIONS: The prevalence of M. pneumoniae pneumonia with virus co-infection and antibiotic prescriptions could differ according to region, although the MRMP pneumonia rate showed no difference within Korea.

Deep Learning-Based Prediction of the 3D Postorthodontic Facial Changes.

With the increase of the adult orthodontic population, there is a need for an accurate and evidence-based prediction of the posttreatment face in 3 dimensions (3D). The objectives of this study are 1) to develop a 3D postorthodontic face prediction method based on a deep learning network using the patient-specific factors and orthodontic treatment conditions and 2) to validate the accuracy and clinical usability of the proposed method. Paired sets (n = 268) of pretreatment (T1) and posttreatment (T2) cone-beam computed tomography (CBCT) of adult patients were trained with a conditional generative adversarial network to generate 3D posttreatment facial data based on the patient's gender, age, and the changes of upper (ΔU1) and lower incisor position (ΔL1) as input. The accuracy was calculated with prediction error and mean absolute distances between real T2 (T2) and predicted T2 (PT2) near 6 perioral landmark regions, as well as percentage of prediction error less than 2 mm using test sets (n = 44). For qualitative evaluation, an online survey was conducted with experienced orthodontists as panels (n = 56). Overall, PT2 indicated similar 3D changes to the T2 face, with the most apparent changes simulated in the perioral regions. The mean prediction error was 1.2 ± 1.01 mm with 80.8% accuracy. More than 50% of the experienced orthodontists were unable to distinguish between real and predicted images. In this study, we proposed a valid 3D postorthodontic face prediction method by applying a deep learning algorithm trained with CBCT data sets.

17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson's disease are associated with LRRC37A/2 expression in astrocytes.

BACKGROUND: Parkinson's disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified. METHODS: To better understand the genetic contribution of this region to PD and to identify novel mechanisms conferring risk for the disease, we fine-mapped the 17q21.31 locus by constructing discrete haplotype blocks from genetic data. We used digital PCR to assess copy number variation associated with PD-associated blocks, and used human brain postmortem RNA-seq data to identify candidate genes that were then further investigated using in vitro models and human brain tissue. RESULTS: We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble α-synuclein, and co-localized with Lewy bodies in PD brain tissue. CONCLUSION: These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with α-synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types.

COVID-19 susceptibility and clinical outcomes in autoimmune inflammatory rheumatic diseases (AIRDs): a systematic review and meta-analysis.

OBJECTIVE: This meta-analysis aims to assess the susceptibility to and clinical outcomes of COVID-19 in autoimmune inflammatory rheumatic disease (AIRD) and following AIRD drug use. MATERIALS AND METHODS: We included observational and case-controlled studies assessing susceptibility and clinical outcomes of COVID-19 in patients with AIRD as well as the clinical outcomes of COVID-19 with or without use of steroids and conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). RESULTS: Meta-analysis including three studies showed that patients with AIRD are not more susceptible to COVID-19 compared to patients without AIRD or the general population (OR: 1.11, 95% CI: 0.58 to 2.14). Incidence of severe outcomes of COVID-19 (OR: 1.34, 95% CI: 0.76 to 2.35) and COVID-19 related death (OR: 1.21, 95% CI: 0.68 to 2.16) also did not show significant difference. The clinical outcomes of COVID-19 among AIRD patients with and without csDMARD or steroid showed that both use of steroid (OR: 1.69, 95% CI: 0.96 to 2.98) or csDMARD (OR: 1.35, 95% CI: 0.63 to 3.08) had no effect on clinical outcomes of COVID-19. CONCLUSIONS: AIRD does not increase susceptibility to COVID-19, not affecting the clinical outcome of COVID-19. Similarly, the use of steroids or csDMARDs for AIRD does not worsen the clinical outcome.