SwiftTron: An Efficient Hardware Accelerator for Quantized Transformers

Transformers' compute-intensive operations pose enormous challenges for their deployment in resource-constrained EdgeAI / tinyML devices. As an established neural network compression technique, quantization reduces the hardware computational and memory resources. In particular, fixed-point quantization is desirable to ease the computations using lightweight blocks, like adders and multipliers, of the underlying hardware. However, deploying fully-quantized Transformers on existing general-purpose hardware, generic AI accelerators, or specialized architectures for Transformers with floating-point units might be infeasible and/or inefficient. Towards this, we propose SwiftTron, an efficient specialized hardware accelerator designed for Quantized Transformers. SwiftTron supports the execution of different types of Transformers' operations (like Attention, Softmax, GELU, and Layer Normalization) and accounts for diverse scaling factors to perform correct computations. We synthesize the complete SwiftTron architecture in a $65$ nm CMOS technology with the ASIC design flow. Our Accelerator executes the RoBERTa-base model in 1.83 ns, while consuming 33.64 mW power, and occupying an area of 273 mm^2. To ease the reproducibility, the RTL of our SwiftTron architecture is released at https://github.com/albertomarchisio/SwiftTron.Comment: To appear at the 2023 International Joint Conference on Neural Networks (IJCNN), Queensland, Australia, June 202

Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach

ObjectiveBreast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification.MethodsIn this retrospective study, four readers labelled four-view mammograms as BAC positive (BAC+) or BAC negative (BAC-) at image level. Starting from a pretrained VGG16 model, we trained a convolutional neural network to discriminate BAC+ and BAC- mammograms. Accuracy, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) were used to assess the diagnostic performance. Predictions of calcified areas were generated using the generalized gradient-weighted class activation mapping (Grad-CAM++) method, and their correlation with manual measurement of BAC length in a subset of cases was assessed using Spearman rho.ResultsA total 1493 women (198 BAC+) with a median age of 59 years (interquartile range 52-68) were included and partitioned in a training set of 410 cases (1640 views, 398 BAC+), validation set of 222 cases (888 views, 89 BAC+), and test set of 229 cases (916 views, 94 BAC+). The accuracy, F1 score, and AUC-ROC were 0.94, 0.86, and 0.98 in the training set; 0.96, 0.74, and 0.96 in the validation set; and 0.97, 0.80, and 0.95 in the test set, respectively. In 112 analyzed views, the Grad-CAM++ predictions displayed a strong correlation with BAC measured length (rho = 0.88, p < 0.001).ConclusionOur model showed promising performances in BAC detection and in quantification of BAC burden, showing a strong correlation with manual measurements

GEN-O-MA project: an Italian network studying clinical course and pathogenic pathways of moyamoya disease—study protocol and preliminary results

Background: GENetics of mOyaMoyA (GEN-O-MA) project is a multicenter observational study implemented in Italy aimed at creating a network of centers involved in moyamoya angiopathy (MA) care and research and at collecting a large series and bio-repository of MA patients, finally aimed at describing the disease phenotype and clinical course as well as at identifying biological or cellular markers for disease progression. The present paper resumes the most important study methodological issues and preliminary results. Methods: Nineteen centers are participating to the study. Patients with both bilateral and unilateral radiologically defined MA are included in the study. For each patient, detailed demographic and clinical as well as neuroimaging data are being collected. When available, biological samples (blood, DNA, CSF, middle cerebral artery samples) are being also collected for biological and cellular studies. Results: Ninety-eight patients (age of onset mean ± SD 35.5 ± 19.6 years; 68.4% females) have been collected so far. 65.3% of patients presented ischemic (50%) and haemorrhagic (15.3%) stroke. A higher female predominance concomitantly with a similar age of onset and clinical features to what was reported in previous studies on Western patients has been confirmed. Conclusion: An accurate and detailed clinical and neuroimaging classification represents the best strategy to provide the characterization of the disease phenotype and clinical course. The collection of a large number of biological samples will permit the identification of biological markers and genetic factors associated with the disease susceptibility in Italy

The Recently Identified P2Y-Like Receptor GPR17 Is a Sensor of Brain Damage and a New Target for Brain Repair

Deciphering the mechanisms regulating the generation of new neurons and new oligodendrocytes, the myelinating cells of the central nervous system, is of paramount importance to address new strategies to replace endogenous damaged cells in the adult brain and foster repair in neurodegenerative diseases. Upon brain injury, the extracellular concentrations of nucleotides and cysteinyl-leukotrienes (cysLTs), two families of endogenous signaling molecules, are markedly increased at the site of damage, suggesting that they may act as “danger signals” to alert responses to tissue damage and start repair. Here we show that, in brain telencephalon, GPR17, a recently deorphanized receptor for both uracil nucleotides and cysLTs (e.g., UDP-glucose and LTD4), is normally present on neurons and on a subset of parenchymal quiescent oligodendrocyte precursor cells. We also show that induction of brain injury using an established focal ischemia model in the rodent induces profound spatiotemporal-dependent changes of GPR17. In the lesioned area, we observed an early and transient up-regulation of GPR17 in neurons expressing the cellular stress marker heat shock protein 70. Magnetic Resonance Imaging in living mice showed that the in vivo pharmacological or biotechnological knock down of GPR17 markedly prevents brain infarct evolution, suggesting GPR17 as a mediator of neuronal death at this early ischemic stage. At later times after ischemia, GPR17 immuno-labeling appeared on microglia/macrophages infiltrating the lesioned area to indicate that GPR17 may also acts as a player in the remodeling of brain circuitries by microglia. At this later stage, parenchymal GPR17+ oligodendrocyte progenitors started proliferating in the peri-injured area, suggesting initiation of remyelination. To confirm a specific role for GPR17 in oligodendrocyte differentiation, the in vitro exposure of cortical pre-oligodendrocytes to the GPR17 endogenous ligands UDP-glucose and LTD4 promoted the expression of myelin basic protein, confirming progression toward mature oligodendrocytes. Thus, GPR17 may act as a “sensor” that is activated upon brain injury on several embryonically distinct cell types, and may play a key role in both inducing neuronal death inside the ischemic core and in orchestrating the local remodeling/repair response. Specifically, we suggest GPR17 as a novel target for therapeutic manipulation to foster repair of demyelinating wounds, the types of lesions that also occur in patients with multiple sclerosis

Twelve Variants Polygenic Score for Low-Density Lipoprotein Cholesterol Distribution in a Large Cohort of Patients With Clinically Diagnosed Familial Hypercholesterolemia With or Without Causative Mutations

: Background A significant proportion of individuals clinically diagnosed with familial hypercholesterolemia (FH), but without any disease-causing mutation, are likely to have polygenic hypercholesterolemia. We evaluated the distribution of a polygenic risk score, consisting of 12 low-density lipoprotein cholesterol (LDL-C)-raising variants (polygenic LDL-C risk score), in subjects with a clinical diagnosis of FH. Methods and Results Within the Lipid Transport Disorders Italian Genetic Network (LIPIGEN) study, 875 patients who were FH-mutation positive (women, 54.75%; mean age, 42.47±15.00 years) and 644 patients who were FH-mutation negative (women, 54.21%; mean age, 49.73±13.54 years) were evaluated. Patients who were FH-mutation negative had lower mean levels of pretreatment LDL-C than patients who were FH-mutation positive (217.14±55.49 versus 270.52±68.59 mg/dL, P<0.0001). The mean value (±SD) of the polygenic LDL-C risk score was 1.00 (±0.18) in patients who were FH-mutation negative and 0.94 (±0.20) in patients who were FH-mutation positive (P<0.0001). In the receiver operating characteristic analysis, the area under the curve for recognizing subjects characterized by polygenic hypercholesterolemia was 0.59 (95% CI, 0.56-0.62), with sensitivity and specificity being 78% and 36%, respectively, at 0.905 as a cutoff value. Higher mean polygenic LDL-C risk score levels were observed among patients who were FH-mutation negative having pretreatment LDL-C levels in the range of 150 to 350 mg/dL (150-249 mg/dL: 1.01 versus 0.91, P<0.0001; 250-349 mg/dL: 1.02 versus 0.95, P=0.0001). A positive correlation between polygenic LDL-C risk score and pretreatment LDL-C levels was observed among patients with FH independently of the presence of causative mutations. Conclusions This analysis confirms the role of polymorphisms in modulating LDL-C levels, even in patients with genetically confirmed FH. More data are needed to support the use of the polygenic score in routine clinical practice

Refinement of the diagnostic approach for the identification of children and adolescents affected by familial hypercholesterolemia: Evidence from the LIPIGEN study

Background and aims: We aimed to describe the limitations of familiar hypercholesterolemia (FH) diagnosis in childhood based on the presence of the typical features of FH, such as physical sings of cholesterol accumulation and personal or family history of premature cardiovascular disease or hypercholesterolemia, comparing their prevalence in the adult and paediatric FH population, and to illustrate how additional information can lead to a more effective diagnosis of FH at a younger age.Methods: From the Italian LIPIGEN cohort, we selected 1188 (&gt;= 18 years) and 708 (&lt;18 years) genetically-confirmed heterozygous FH, with no missing personal FH features. The prevalence of personal and familial FH features was compared between the two groups. For a sub-group of the paediatric cohort (N = 374), data about premature coronary heart disease (CHD) in second-degree family members were also included in the evaluation.Results: The lower prevalence of typical FH features in children/adolescents vs adults was confirmed: the prevalence of tendon xanthoma was 2.1% vs 13.1%, and arcus cornealis was present in 1.6% vs 11.2% of the cohorts, respectively. No children presented clinical history of premature CHD or cerebral/peripheral vascular disease compared to 8.8% and 5.6% of adults, respectively. The prevalence of premature CHD in first-degree relatives was significantly higher in adults compared to children/adolescents (38.9% vs 19.7%). In the sub-cohort analysis, a premature CHD event in parents was reported in 63 out of 374 subjects (16.8%), but the percentage increased to 54.0% extending the evaluation also to second-degree relatives.Conclusions: In children, the typical FH features are clearly less informative than in adults. A more thorough data collection, adding information about second-degree relatives, could improve the diagnosis of FH at younger age

Spectrum of mutations in Italian patients with familial hypercholesterolemia: New results from the LIPIGEN study

Background Familial hypercholesterolemia (FH) is an autosomal dominant disease characterized by elevated plasma levels of LDL-cholesterol that confers an increased risk of premature atherosclerotic cardiovascular disease. Early identification and treatment of FH patients can improve prognosis and reduce the burden of cardiovascular mortality. Aim of this study was to perform the mutational analysis of FH patients identified through a collaboration of 20 Lipid Clinics in Italy (LIPIGEN Study). Methods We recruited 1592 individuals with a clinical diagnosis of definite or probable FH according to the Dutch Lipid Clinic Network criteria. We performed a parallel sequencing of the major candidate genes for monogenic hypercholesterolemia (LDLR, APOB, PCSK9, APOE, LDLRAP1, STAP1). Results A total of 213 variants were detected in 1076 subjects. About 90% of them had a pathogenic or likely pathogenic variants. More than 94% of patients carried pathogenic variants in LDLR gene, 27 of which were novel. Pathogenic variants in APOB and PCSK9 were exceedingly rare. We found 4 true homozygotes and 5 putative compound heterozygotes for pathogenic variants in LDLR gene, as well as 5 double heterozygotes for LDLR/APOB pathogenic variants. Two patients were homozygous for pathogenic variants in LDLRAP1 gene resulting in autosomal recessive hypercholesterolemia. One patient was found to be heterozygous for the ApoE variant p.(Leu167del), known to confer an FH phenotype. Conclusions This study shows the molecular characteristics of the FH patients identified in Italy over the last two years. Full phenotypic characterization of these patients and cascade screening of family members is now in progress

Lipoprotein(a) Genotype Influences the Clinical Diagnosis of Familial Hypercholesterolemia

: Background Evidence suggests that LPA risk genotypes are a possible contributor to the clinical diagnosis of familial hypercholesterolemia (FH). This study aimed at determining the prevalence of LPA risk variants in adult individuals with FH enrolled in the Italian LIPIGEN (Lipid Transport Disorders Italian Genetic Network) study, with (FH/M+) or without (FH/M-) a causative genetic variant. Methods and Results An lp(a) [lipoprotein(a)] genetic score was calculated by summing the number risk-increasing alleles inherited at rs3798220 and rs10455872 variants. Overall, in the 4.6% of 1695 patients with clinically diagnosed FH, the phenotype was not explained by a monogenic or polygenic cause but by genotype associated with high lp(a) levels. Among 765 subjects with FH/M- and 930 subjects with FH/M+, 133 (17.4%) and 95 (10.2%) were characterized by 1 copy of either rs10455872 or rs3798220 or 2 copies of either rs10455872 or rs3798220 (lp(a) score ≥1). Subjects with FH/M- also had lower mean levels of pretreatment low-density lipoprotein cholesterol than individuals with FH/M+ (t test for difference in means between FH/M- and FH/M+ groups &lt;0.0001); however, subjects with FH/M- and lp(a) score ≥1 had higher mean (SD) pretreatment low-density lipoprotein cholesterol levels (223.47 [50.40] mg/dL) compared with subjects with FH/M- and lp(a) score=0 (219.38 [54.54] mg/dL for), although not statistically significant. The adjustment of low-density lipoprotein cholesterol levels based on lp(a) concentration reduced from 68% to 42% the proportion of subjects with low-density lipoprotein cholesterol level ≥190 mg/dL (or from 68% to 50%, considering a more conservative formula). Conclusions Our study supports the importance of measuring lp(a) to perform the diagnosis of FH appropriately and to exclude that the observed phenotype is driven by elevated levels of lp(a) before performing the genetic test for FH

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score &gt; 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p &lt; 0.001), RR = 2.19 for ICU admission (p &lt; 0.001), and RR = 2.43 for death (p &lt; 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon