Attention-enhanced dilated convolution for Parkinson's disease detection using transcranial sonography.

BACKGROUND: Transcranial sonography (TCS) plays a crucial role in diagnosing Parkinson's disease. However, the intricate nature of TCS pathological features, the lack of consistent diagnostic criteria, and the dependence on physicians' expertise can hinder accurate diagnosis. Current TCS-based diagnostic methods, which rely on machine learning, often involve complex feature engineering and may struggle to capture deep image features. While deep learning offers advantages in image processing, it has not been tailored to address specific TCS and movement disorder considerations. Consequently, there is a scarcity of research on deep learning algorithms for TCS-based PD diagnosis. METHODS: This study introduces a deep learning residual network model, augmented with attention mechanisms and multi-scale feature extraction, termed AMSNet, to assist in accurate diagnosis. Initially, a multi-scale feature extraction module is implemented to robustly handle the irregular morphological features and significant area information present in TCS images. This module effectively mitigates the effects of artifacts and noise. When combined with a convolutional attention module, it enhances the model's ability to learn features of lesion areas. Subsequently, a residual network architecture, integrated with channel attention, is utilized to capture hierarchical and detailed textures within the images, further enhancing the model's feature representation capabilities. RESULTS: The study compiled TCS images and personal data from 1109 participants. Experiments conducted on this dataset demonstrated that AMSNet achieved remarkable classification accuracy (92.79%), precision (95.42%), and specificity (93.1%). It surpassed the performance of previously employed machine learning algorithms in this domain, as well as current general-purpose deep learning models. CONCLUSION: The AMSNet proposed in this study deviates from traditional machine learning approaches that necessitate intricate feature engineering. It is capable of automatically extracting and learning deep pathological features, and has the capacity to comprehend and articulate complex data. This underscores the substantial potential of deep learning methods in the application of TCS images for the diagnosis of movement disorders.

Expressional respones of hsp70 genes against abiotic and entomopathgenic stresses in four different noctuid larval species (Lepidoptera: Noctidae).

Heat shock proteins (Hsps) are stress response proteins. In a previous study, host larval Hsp70s were identified as the structural proteins of virions of Heliothis virescens ascovirus 3h (HvAV-3h), an insect virus that mainly infects noctuid larvae. To investigate the response of hsp70s of healthy Mythimna separata, Spodoptera exigua, Spodoptera frugiperda, and Spodoptera litura larvae to various abiotic or entomopathogenic stresses, quantitative PCR was used to detect larval hsp70s expression patterns. Results showed distinct expression patterns of hsp70s in response to different abiotic stresses. Notably, Mshsp70 expression pattern resembled Slhsp70 under most treatments. In healthy larvae, no tissue tropism was observed concerning the relative expression of Mshsp70, Sfhsp70, and Slhsp70. After infection with HvAV-3h, the expression of hsp70s in all dissected tissues of all tested larval species increased. Significant differences were found in the fat bodies of M. separata, S. exigua, and S. litura as well as in the hemolymph of S. exigua and S. litura. Subsequent silencing of Slhsp70, resulted in a significant decrease in DNA replication levels of HvAV-3h in S. litura larvae at 24 and 72 h post RNA interference, indicating that Slhsp70 is necessary for DNA replication in HvAV-3h. These data can provide references for the studying on the stress response of noctuid larvae to different environmental factors.

Evaluating the efficacy of microalgal-bacterial granular sludge system in lake water remediation.

The microalgal-bacterial granular sludge (MBGS) process is attracting attention as a green wastewater treatment technology. However, research on the application of MBGS in lake water remediation is limited. Thus, this experiment investigated the feasibility and the efficacy of the MBGS process for the treatment of natural lake water in a continuous-flow tubular reactor. The average removal efficiencies of COD, NH4+-N, NO3--N, NO2--N, TN, PO43--P, TP, and turbidity by MBGS system in the day/night cycles were 50.10/61.39%, 63.52/75.23%, 43.37/73.57%, 90.72/93.48%, 78.30/80.02%, 71.13/74.62%, 65.08/70.57%, 92.32/89.84%, respectively. As the experiment progressed, the total chlorophyll content in MBGS decreased as the granule size increased, while the extracellular polymeric substances content increased, suggesting that the lake water contributed to bacterial growth and favored the stability of MBGS. Moreover, the eukaryotic microorganisms were dominated by Chlorophyta and Rotifera, and prokaryotic microorganisms were dominated by Proteobacteria in MBGS. By promoting the decomposition of various organic compounds in the lake water and inhibiting sludge expansion, these microorganisms help the MBGS system to maintain excellent granular characteristics and performance. Overall, the MBGS system proved to be a feasible option for the remediation of natural lake waters.

Increased Free Water in the Substantia Nigra in Asymptomatic LRRK2 G2019S Mutation Carriers.

BACKGROUND: The alteration of substantia nigra (SN) degeneration in populations at risk of Parkinson's disease (PD) is unclear. OBJECTIVE: We investigated free water (FW) values in the posterior SN (pSN) in asymptomatic LRRK2 G2019S mutation carriers. METHODS: We analyzed diffusion imaging data from 28 asymptomatic LRRK2 G2019S mutation carriers and 30 healthy controls (HCs), whereas 11 asymptomatic LRRK2 G2019S carriers and 11 HCs were followed up. FW values in the pSN were measured and compared between the groups. The relationship between longitudinal changes in FW in the pSN and dopamine transporter striatal binding ratio (SBR) was analyzed. RESULTS: FW values in the pSN were significantly elevated and kept increasing during follow-up in asymptomatic LRRK2 G2019S carriers. There was a negative correlation between FW changes in the left pSN and SBR changes in the left putamen. CONCLUSION: FW in the pSN has the potential to be a progression imaging marker of early dopaminergic degeneration in the population at risk of PD. © 2022 International Parkinson and Movement Disorder Society.

Increased Free Water in the Putamen in Idiopathic REM Sleep Behavior Disorder.

BACKGROUND: It has been suggested that the loss of nigrostriatal dopaminergic axon terminals occurs before the loss of dopaminergic neurons in the substantia nigra (SN) in Parkinson's disease (PD). This study aimed to use free-water imaging to evaluate microstructural changes in the dorsoposterior putamen (DPP) of idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) patients, which is considered a prodromal stage of synucleinopathies. METHODS: Free water values in the DPP, dorsoanterior putamen (DAP), and posterior SN were compared between the healthy controls (n = 48), iRBD (n = 43) and PD (n = 47) patients. In iRBD patients, the relationships between baseline and longitudinal free water values and clinical manifestations or dopamine transporter (DAT) striatal binding ratio (SBR) were analyzed. RESULTS: Free water values were significantly higher in the DPP and posterior substantia nigra (pSN), but not in the DAP, in the iRBD and PD groups than in controls. In iRBD patients, free water values in the DPP were progressively increased and correlated with the progression of clinical manifestations and the striatal DAT SBR. Baseline free water in the DPP was negatively correlated with striatal DAT SBR and hyposmia and positively correlated with motor deficits. CONCLUSIONS: This study demonstrates that free water values in the DPP are increased cross-sectionally and longitudinally and associated with clinical manifestations and the function of the dopaminergic system in the prodromal stage of synucleinopathies. Our findings indicate that free-water imaging of the DPP has the potential to be a valid marker of early diagnosis and progression of synucleinopathies. © 2023 International Parkinson and Movement Disorder Society.

Free-Water Imaging of the Substantia Nigra in GBA Pathogenic Variant Carriers.

BACKGROUND: Pathogenic variants in the glucocerebrosidase gene (GBA) have been identified as the most common genetic risk factor for Parkinson's disease (PD). However, the features of substantia nigra damage in GBA pathogenic variant carriers remain unclear. OBJECTIVE: We aimed to evaluate the microstructural changes in the substantia nigra in non-manifesting GBA pathogenic variant carriers (GBA-NMC) and PD patients with GBA pathogenic variant (GBA-PD) with free-water imaging. METHODS: First, we compared free water values in the posterior substantia nigra between non-manifesting non-carriers (NMNC, n = 29), GBA-NMC (n = 26), and GBA-PD (n = 16). Then, free water values in the posterior substantia nigra were compared between GBA-PD and early- (n = 19) and late-onset (n = 40) idiopathic PD (iPD) patients. Furthermore, we examined whether the baseline free water values could predict the progressions of clinical symptoms. RESULTS: The free water values in the posterior substantia nigra were significantly higher in the GBA-NMC and GBA-PD groups compared to NMNC, and were significantly increased in the GBA-PD group than both early- and late-onset iPD. Free water values in the posterior substantia nigra could predict the progression of anxiety and cognitive decline in GBA-NMC and GBA-PD groups. CONCLUSIONS: We demonstrate that free water values are elevated in the substantia nigra and predict the development of non-motor symptoms in GBA-NMC and GBA-PD. Our findings demonstrate that a significant nigral impairment already exists in GBA-NMC, and nigral injury may be more severe in GBA-PD than in iPD. These results support that free-water imaging can as a potential early marker of substantia nigra damage. © 2023 International Parkinson and Movement Disorder Society.

Synaptic Loss in Spinocerebellar Ataxia Type 3 Revealed by SV2A Positron Emission Tomography.

BACKGROUND: Severe reduced synaptic density was observed in spinocerebellar ataxia (SCA) in postmortem neuropathology, but in vivo assessment of synaptic loss remains challenging. OBJECTIVE SPINOCEREBELLAR ATAXIA TYPE 3: The objective of this study was to assess in vivo synaptic loss and its clinical correlates in spinocerebellar ataxia type 3 (SCA3) patients by synaptic vesicle glycoprotein 2A (SV2A)-positron emission tomography (PET) imaging. METHODS: We recruited 74 SCA3 individuals including preataxic and ataxic stages and divided into two cohorts. All participants received SV2A-PET imaging using 18 F-SynVesT-1 for synaptic density assessment. Specifically, cohort 1 received standard PET procedure and quantified neurofilament light chain (NfL), and cohort 2 received simplified PET procedure for exploratory purpose. Bivariate correlation was performed between synaptic loss and clinical as well as genetic assessments. RESULTS: In cohort 1, significant reductions of synaptic density were observed in cerebellum and brainstem in SCA3 ataxia stage compared to preataxic stage and controls. Vermis was found significantly involved in preataxic stage compared to controls. Receiver operating characteristic (ROC) curves highlighted SV2A of vermis, pons, and medulla differentiating preataxic stage from ataxic stage, and SV2A combined with NfL improved the performance. Synaptic density was significantly negatively correlated with disease severity in cerebellum and brainstem (International Co-operative Ataxia Rating Scale: ρ ranging from -0.467 to -0.667, P ≤ 0.002; Scale of Assessment and Rating of Ataxia: ρ ranging from -0.465 to -0.586, P ≤ 0.002). SV2A reduction tendency of cerebellum and brainstem identified in cohort 1 was observed in cohort 2 with simplified PET procedure. CONCLUSIONS: We first identified in vivo synaptic loss was related to disease severity of SCA3, suggesting SV2A PET could be a promising clinical biomarker for disease progression of SCA3. © 2023 International Parkinson and Movement Disorder Society.

Recent advances of LSD1/KDM1A inhibitors for disease therapy.

Lysine-specific demethylase 1 (LSD1/KDM1A) dysregulation is closely associated with the pathological processes of various diseases, especially hematologic malignancies. Significant progresses have been made in the field of LSD1-targeted drug discovery. Nine LSD1 inhibitors including tranylcypromine, ORY-1001, ORY-2001, GSK-2879552, IMG-7289, INCB059872, TAK-418, CC-90011 and SP-2577 have entered clinical stage for disease treatment as either mono- or combinational therapy. This review updates LSD1 inhibitors reported during 2022. Design strategies, structure-activity relationship studies, binding model analysis and modes of action are highlighted. In particular, the unique multiple-copies binding mode of quinazoline derivatives paves new ways for the development of reversible LSD1 inhibitors by blocking the substrate entrance. The design strategy of clinical candidate TAK-418 also provides directions for further optimization of novel irreversible LSD1 inhibitors with low hematological side effects. The influence of the stereochemistry on the potency against LSD1 and its homolog LSD2 is briefly discussed. Finally, the challenges and prospects of LSD1-targeted drug discovery are also given.

Idiopathic multicentric castleman's disease mimicking immunoglobulin G4-related disease responding well to Bortezomib: a case report.

BACKGROUND: Castleman's disease (CD) is a rare disease that has clinical and pathological similarities to lymphoma and is characterized by a high frequency of associated immunological dysfunction. ImmunoglobulinG4-related disease (IgG4-RD) is a collection of systemic disorders that affect numerous organs and are also referred to as IgG4-associated sclerosing diseases. CD and IgG4-RD are difficult to separate because they may manifest similar commin clinical features. CASE PRESENTATION: This case describes a 53-year-old female who, during routine medical check-up, exhibited a progressive increase in serum globulin levels and a simultaneous worsening of anemia symptoms, raising concern for a clonal plasma cell disease such as myeloma. However, bone marrow punctures did not reveal any abnormal plasma cells. Also, serum and urine immunofixation electrophoresis demonstrated no abnormal monoclonal protein bands. In addition, several laboratory findings excluded chronic liver disease, chronic infections caused by bacteria or viruses. Later, we found elevated serum IgG4 levels (10,700 mg/L), and identified multiple enlarged lymph nodes throughout the patient's body. Axillary lymph node aspiration revealed no abnormal lymphocytes, ruling out the possibility of lymphoma. Pathological morphology of the axillary lymph revealed a large number of plasma cells in the lymphatic follicles. In addition, there was a reduction in lymphatic follicle size and apoptosis of the germinal centres. Immunohistochemistry revealed IgG4+/IgG + in > 40% of cells, and more than 100 IgG4 + cells per high powered field (HPF) of specimen. As of now, finding strongly suggested IgG4-RD. This patient was treated with glucocorticoids and various immunosuppressive drugs, such as prednisone, cyclosporine, methotrexate, cyclophosphamide, mycophenolate mofetil, azathioprine and hydroxychloroquine. Unfortunately, the patient did not recover. Ultimately, idiopathic multicentric Castleman disease (iMCD) was diagnosed in relation to the patient's clinical presentation and laboratory tests, and after combination chemotherapy (VCD: Bortezomib, Cyclophosphamide and Dexamethasone), durable remission was achieved without serious adverse effects. During the follow-up period of one year and ten months, the patient remained stable. CONCLUSION: The diagnosis of Castleman must be distinguished from other disorders such as IgG4-RD, malignant lymphoma, reactive hyperplasia of various lymph nodes (mostly caused by viral infections), plasmacytoma, advanced HIV and rheumatic diseases. Besides observing systemic symptoms, laboratory tests such as immunoglobulin levels, complement levels, interleukin levels, and C-reactive protein levels should also be performed in order to determine a diagnosis.

The Prognostic Value and Potential Mechanism of Tumor-Nutrition-Inflammation Index and Genes in Patients with Advanced Lung Cancer.

Background: Lung cancer (LC) has the highest mortality rate all over the world. It is necessary to search for novel potential biomarkers that are easily accessible and inexpensive in identifying patients with LC at early stage. Methods: A total of 195 patients with advanced LC who have received first-line chemotherapy were involved in this study. The optimized cut-off values of AGR and SIRI (AGR = albumin/globulin; SIRI = neutrophil ∗ monocyte/lymphocyte) were determined by survival function analysis based on R software. COX regression analysis was performed to obtain the independent factors for establishing the nomogram model. A nomogram model comprising these independent prognostic parameters was built for the TNI (tumor-nutrition-inflammation index) score calculation. The predictive accuracy was demonstrated through ROC curve and calibration curves after index concordance. Results: The optimized cut-off values of AGR and SIRI were 1.22 and 1.60, respectively. It was revealed that liver metastasis, SCC, AGR, and SIRI were independent prognostic factors in advanced lung cancer by Cox analysis. Afterwards, the nomogram model comprised of these independent prognostic parameters was built for TNI scores calculation. Based on the TNI quartile values, patients were divided into four groups. And it was indicated that higher TNI had worse OS (P < 0.05) via Kaplan-Meier analysis and log-rank test. Moreover, the C-index and 1-year AUC area were 0.756 (0.723-0.788) and 75.62, respectively. There was high consistency shown in the calibration curves between predicted and actual survival proportions in the TNI model. In addition, tumor-nutrition-inflammation index and genes play an important role in LC development that might affect some pathways related to tumor development including cell cycle, homologous recombination, and P53 signaling pathway from a molecular level. Conclusion: TNI might be an analytical tool which was practical and precise for survival prediction of patients with advanced LC. Tumor-nutrition-inflammation index and genes play an important role in LC development. A preprint has previously been published [1].

Towards in vivo ground truth susceptibility for single-orientation deep learning QSM: A multi-orientation gradient-echo MRI dataset.

Recently, deep neural networks have shown great potential for solving dipole inversion of quantitative susceptibility mapping (QSM) with improved results. However, these studies utilized their limited dataset for network training and inference, which may lead to untrustworthy conclusions. Thus, a common dataset is needed for a fair comparison between different QSM reconstruction networks. Additionally, finding an in vivo reference susceptibility map that matches acquired single-orientation phase data remains an open problem. Susceptibility tensor imaging (STI) χ33 and Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS) are considered reference susceptibility candidates. However, a large number of multi-orientation GRE data for both STI and COSMOS reconstruction are now unavailable for training supervised neural networks for QSM. In this study, we reported the largest multi-orientation dataset, to the best of our knowledge in the QSM research field, with a total of 144 scans from 8 healthy subjects collected using a 3D GRE sequence from the same MR scanner. In addition, the parcellation of deep gray matter is also provided for automatically extracting susceptibility values. Five recently developed deep neural networks, i.e., xQSM, QSMnet, autoQSM, LPCNN, and MoDL-QSM were performed on this dataset. This potential data source could provide a common framework and labels to test the accuracy and robustness of deep neural networks for QSM reconstruction. This dataset has the potential to provide a benchmark of reference susceptibility for the deep learning-based QSM methods. Additionally, the trained COSMOS-labeled and χ33-labeled networks were tested on the pathological data to explore their potential applications. The data together with deep gray matter parcellation maps are now publicly available via an open repository at https://osf.io/yfms7/, and the raw multi-orientation GRE data are also available at https://osf.io/y6rc3/.

The progression rate of spinocerebellar ataxia type 3 varies with disease stage.

BACKGROUND: In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions. METHODS: Data were derived from the longest longitudinal study, with 642 examinations by International Cooperative Ataxia Rating Scale (ICARS) from 82 SCA3 participants. Using different time scales of disease duration, we performed multiple different linear, quadratic and piece-wise linear growth models to fit the relationship between ICARS scores and duration. Models comparison was employed to determine the best-fitting model according to goodness-of-fit tests, and the analysis of variance among nested models. RESULTS: An acceleration was detected after 13 years of duration: ICARS scores progressed 2.445 (SE: 0.185) points/year before and 3.547 (SE: 0.312) points/year after this deadline. Piece-wise growth model fitted better to studied data than other two types of models. The length of expanded CAG repeat (CAGexp) in ATXN3 gene significantly influenced progression. Age at onset of gait ataxia (AOga), a proxy for aging process, was not an independent modifier but affected the correlation between CAGexp and progression. Additionally, gender had no significant effect on progression rate of ICARS. The piece-wise growth models were determined as the predictive models, and ICARS predictions from related models were available. CONCLUSIONS: We first confirmed that ICARS progressed as a nonlinear pattern and varied according to different stages in SCA3. In addition to ATXN3 CAGexp, AOga or aging process regulated the progression by interacting with CAGexp.

Unique design approach to realize an O-band laser monolithically integrated on 300†mm Si substrate by nano-ridge engineering.

We introduce a new design space for optimizing III-V devices monolithically grown on Silicon substrates by extending the concept of nano-ridge engineering from binary semiconductors such as GaAs, InAs and GaSb to the ternary alloy InGaAs. This allows controlling the fundamental lattice constant of the fully relaxed ternary nano-ridge which thereby serves as a tunable base for the integration of diverse device hetero-layers. To demonstrate the flexibility of this approach, we realized an O-band nano-ridge laser containing three In0.45Ga0.55As quantum wells, which are pseudomorphically strained to an In0.25Ga0.75As nano-ridge base. The demonstration of an optically pumped nano-ridge laser operating around 1300 nm underlines the potential of this cost-efficient and highly scalable integration approach for silicon photonics.

Blood Neurofilament Light Chain in Genetic Ataxia: A Meta-Analysis.

BACKGROUND: No comprehensive meta-analysis has ever been performed to assess the value of neurofilament light chain (NfL) as a biomarker in genetic ataxia. OBJECTIVE: We conducted a meta-analysis to summarize NfL concentration and evaluate its utility as a biomarker in genetic ataxia. METHODS: Studies were included if they reported NfL concentration of genetic ataxia. We used log (mean ± SD) NfL to describe mean raw value of NfL. The effect size of NfL between genetic ataxia and healthy controls (HC) was expressed by mean difference. Correlation between NfL and disease severity was calculated. RESULTS: We identified 11 studies of 624 HC and 1006 patients, here referred to as spinocerebellar ataxia (SCA1, 2, 3, 6, and 7), Friedreich ataxia (FRDA), and ataxia telangiectasia (A-T). The concentration of blood NfL (bNfL) elevated with proximity to expected onset, and progressively increased from asymptomatic to preclinical to clinical stage in SCA3. Compared with HC, bNfL levels were significantly higher in SCA1, 2, 3, and 7, FRDA, as well as A-T, and the difference increased with the advancing disease in SCA3. bNfL levels correlated with disease severity in SCA3. There was a significant correlation between bNfL and longitudinal progression in SCA3. Additionally, bNfL increased with age in HC, yet this is probably masked by higher disease-related effects on bNfL in genetic ataxia. CONCLUSIONS: bNfL can be used as a potential biomarker to predict disease onset, severity, and progression of genetic ataxia. Reference-value setting of bNfL should be divided according to age. © 2021 International Parkinson and Movement Disorder Society.

Identification of the Largest SCA36 Pedigree in Asia: with Multimodel Neuroimaging Evaluation for the First Time.

Spinocerebellar ataxias (SCAs) are a large group of hereditary neurodegenerative diseases characterized by ataxia and dysarthria. Due to high clinical and genetic heterogeneity, many SCA families are undiagnosed. Herein, using linkage analysis, WES, and RP-PCR, we identified the largest SCA36 pedigree in Asia. This pedigree showed some distinct clinical characteristics. Cognitive impairment and gaze palsy are common and severe in SCA36 patients, especially long-course patients. Although no patients complained of hearing loss, most of them presented with hearing impairment in objective auxiliary examination. Voxel-based morphometry (VBM) demonstrated a reduction of volumes in cerebellum, brainstem, and thalamus (corrected P < 0.05). Reduced volumes in cerebellum were also found in presymptomatic carriers. Resting-state functional MRI (R-fMRI) found reduced ReHo values in left cerebellar posterior lobule (corrected P < 0.05). Diffusion tensor imaging (DTI) demonstrated a reduction of FA values in cerebellum, midbrain, superior and inferior cerebellar peduncle (corrected P < 0.05). MRS found reduced NAA/Cr values in cerebellar vermis and hemisphere (corrected P < 0.05). Our findings could provide new insights into management of SCA36 patients. Detailed auxiliary examination are recommended to assess hearing or peripheral nerve impairment, and we should pay more attention to eye movement and cognitive changes in patients. Furthermore, for the first time, our multimodel neuroimaging evaluation generate a full perspective of brain function and structure in SCA36 patients.

Isoeugenol-functionalized nanogels inhibit peri-implantitis associated bacteria in vitro.

OBJECTIVES: Obligate and facultative anaerobic bacteria adhering to dental implants are a major cause for peri-implant inflammation, which, if left untreated, can lead to implant loss. Previously, our group developed a new route for the synthesis of isoeugenol-functionalized aqueous nanogels for implant coatings. METHODS: Here, the antimicrobial activity of several new nanogels differing in spacer length (n = 6, 9, 44), radius (60-200 nm), and amount of isoeugenol functional substance (1-20 mol%) was tested against the following peri-implantitis-associated species: Fusobacterium nucleatum, Porphyromonas gingivalis, Prevotella intermedia, Aggregatibacter actinomycetemcomitans, Escherichia coli, Actinomyces viscosus, Enterococcus faecalis, Staphylococcus aureus, Streptococcus oralis, S. parasanguinis, and the yeast Candida albicans. The minimal bactericidal concentration (MBC) and fungicidal concentration (MFC) were determined for each combination. In addition, transmission electron microscopy (TEM) and fluorescence microscopy after live-dead-staining (LD-S) were performed to visualize nanogel-microbe interactions. RESULTS: Two nanogels, NG9-3 and NG9-4 (colloids of 80-150 nm, with a spacer length of n = 9 and feeding between 5 and 10 mol% isoeugenol), had an inhibitory effect on all Gram-positive species and on P. gingivalis and P. intermedia with MBC ≥31.25 µg/ml. TEM and LD-S images showed that cellular adhesion and uptake of nanogels resulted in swelling, shedding, or even complete detachment of the cell wall and then to bursting (see graphical abstract). CONCLUSIONS: Functional nanogels can be used as building blocks in the design of bioactive coatings on implants to prevent infection and accelerate tissue regeneration, but the concentrations required are higher than for antibiotics.

MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping.

Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms (χ13, χ23 and χ33) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ33 and phase induced by χ13 and χ23 terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications.

Biallelic Intronic AAGGG Expansion of RFC1 is Related to Multiple System Atrophy.

OBJECTIVE: A recessive biallelic repeat expansion, (AAGGG)exp , in the RFC1 gene has been reported to be a frequent cause of late-onset ataxia. For cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS), the recessive biallelic (AAGGG)exp genotype was present in ~92% of cases. This study aimed to examine whether the pentanucleotide repeat (PNR) was related to multiple system atrophy (MSA), which shares a spectrum of symptoms with CANVAS. METHODS: In this study, we screened the pathogenic (AAGGG)exp repeat and 5 other PNRs in 104 Chinese sporadic adult-onset ataxia of unknown aetiology (SAOA) patients, 282 MSA patients, and 203 unaffected individuals. Multiple molecular genetic tests were used, including long-range polymerase chain reaction (PCR), repeat-primed PCR (RP-PCR), Sanger sequencing, and Southern blot. Comprehensive clinical assessments were conducted, including neurological examination, neuroimaging, nerve electrophysiology, and examination of vestibular function. RESULTS: We identified biallelic (AAGGG)exp in 1 SAOA patient and 3 MSA patients. Additionally, 1 MSA patient had the (AAGGG)exp /(AAAGG)exp genotype with uncertain pathogenicity. We also described the carrier frequency for different PNRs in our cohorts. Furthermore, we summarized the distinct phenotypes of affected patients, suggesting that biallelic (AAGGG)exp in RFC1 could be associated with MSA and should be screened routinely in the MSA diagnostic workflow. INTERPRETATION: Our results expanded the clinical phenotypic spectrum of RFC1-related disorders and raised the possibility that MSA might share the same genetic background as CANVAS, which is crucial for re-evaluating the current CANVAS and MSA diagnostic criteria. ANN NEUROL 2020;88:1132-1143.

Loss-coupled DFB nano-ridge laser monolithically grown on a standard 300-mm Si wafer.

We present a loss-coupled distributed feedback microlaser, monolithically grown on a standard 300-mm Si wafer using nano-ridge engineering. The cavity is formed by integrating a metallic grating on top of the nano-ridge. This allows forming a laser cavity without etching the III-V material, avoiding damaged interfaces and the associated carrier loss. Simulations, supported by experimental characterisation of the modal gain of the nano-ridge devices, predict an optimal duty cycle for the grating of ~0.4, providing a good trade-off between coupling strength and cavity loss for the lasing mode. The model was experimentally verified by characterising the lasing threshold and external efficiency of devices exhibiting gratings with varying duty cycle. The high modal gain and low threshold obtained prove the excellent quality of the epitaxial material. Furthermore, the low loss metal grating might provide a future route to electrical injection and efficient heat dissipation of these nanoscale devices.

Prediction of the Age at Onset of Spinocerebellar Ataxia Type 3 with Machine Learning.

BACKGROUND: In polyglutamine (polyQ) disease, the investigation of the prediction of a patient's age at onset (AAO) facilitates the development of disease-modifying intervention and underpins the delay of disease onset and progression. Few polyQ disease studies have evaluated AAO predicted by machine-learning algorithms and linear regression methods. OBJECTIVE: The objective of this study was to develop a machine-learning model for AAO prediction in the largest spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) population from mainland China. METHODS: In this observational study, we introduced an innovative approach by systematically comparing the performance of 7 machine-learning algorithms with linear regression to explore AAO prediction in SCA3/MJD using CAG expansions of 10 polyQ-related genes, sex, and parental origin. RESULTS: Similar prediction performance of testing set and training set in each models were identified and few overfitting of training data was observed. Overall, the machine-learning-based XGBoost model exhibited the most favorable performance in AAO prediction over the traditional linear regression method and other 6 machine-learning algorithms for the training set and testing set. The optimal XGBoost model achieved mean absolute error, root mean square error, and median absolute error of 5.56, 7.13, 4.15 years, respectively, in testing set 1, with mean absolute error (4.78 years), root mean square error (6.31 years), and median absolute error (3.59 years) in testing set 2. CONCLUSION: Machine-learning algorithms can be used to predict AAO in patients with SCA3/MJD. The optimal XGBoost algorithm can provide a good reference for the establishment and optimization of prediction models for SCA3/MJD or other polyQ diseases. © 2020 International Parkinson and Movement Disorder Society.