Context-Aware Seeds for Read Mapping

Motivation: Most modern seed-and-extend NGS read mappers employ a seeding scheme that requires extracting t non-overlapping seeds in each read in order to find all valid mappings under an edit distance threshold of t. As t grows (such as in long reads with high error rate), this seeding scheme forces mappers to use more and shorter seeds, which increases the seed hits (seed frequencies) and therefore reduces the efficiency of mappers. Results: We propose a novel seeding framework, context-aware seeds (CAS). CAS guarantees finding all valid mapping but uses fewer (and longer) seeds, which reduces seed frequencies and increases efficiency of mappers. CAS achieves this improvement by attaching a confidence radius to each seed in the reference. We prove that all valid mappings can be found if the sum of confidence radii of seeds are greater than t. CAS generalizes the existing pigeonhole-principle-based seeding scheme in which this confidence radius is implicitly always 1. Moreover, we design an efficient algorithm that constructs the confidence radius database in linear time. We experiment CAS with E. coli genome and show that CAS reduces seed frequencies by up to 20.3% when compared with the state-of-the-art pigeonhole-principle-based seeding algorithm, the Optimal Seed Solver. Availability: https://github.com/Kingsford-Group/CAS_cod

MPCFormer: fast, performant and private Transformer inference with MPC

Enabling private inference is crucial for many cloud inference services that are based on Transformer models. However, existing private inference solutions for Transformers can increase the inference latency by more than 60x or significantly compromise the quality of inference results. In this paper, we design the framework MPCFORMER using secure multi-party computation (MPC) and Knowledge Distillation (KD). It can be used in tandem with many specifically designed MPC-friendly approximations and trained Transformer models. MPCFORMER significantly speeds up Transformer model inference in MPC settings while achieving similar ML performance to the input model. We evaluate MPCFORMER with various settings in MPC. On the IMDb dataset, we achieve similar performance to BERTBASE, while being 5.3x faster. On the GLUE benchmark, we achieve 97% performance of BERTBASE with a 2.2x speedup. We show that MPCFORMER remains effective with different trained Transformer weights such as ROBERTABASE and larger models including BERTLarge. In particular, we achieve similar performance to BERTLARGE, while being 5.93x faster on the IMDb dataset

TensorIR: An Abstraction for Automatic Tensorized Program Optimization

Deploying deep learning models on various devices has become an important topic. The wave of hardware specialization brings a diverse set of acceleration primitives for multi-dimensional tensor computations. These new acceleration primitives, along with the emerging machine learning models, bring tremendous engineering challenges. In this paper, we present TensorIR, a compiler abstraction for optimizing programs with these tensor computation primitives. TensorIR generalizes the loop nest representation used in existing machine learning compilers to bring tensor computation as the first-class citizen. Finally, we build an end-to-end framework on top of our abstraction to automatically optimize deep learning models for given tensor computation primitives. Experimental results show that TensorIR compilation automatically uses the tensor computation primitives for given hardware backends and delivers performance that is competitive to state-of-art hand-optimized systems across platforms.Comment: Accepted to ASPLOS 202

Better PROMs and higher return-to-sport rate after modular bicompartmental knee arthroplasty than after total knee arthroplasty for medial and patellofemoral compartment osteoarthritis

BackgroundTheoretical advantages of bicompartmental knee arthroplasty (BKA) over total knee arthroplasty (TKA) for bicompartmental (medial combined with patellofemoral) osteoarthritis (OA) are still unclear. This study aimed to compare patient-reported outcome measures (PROMs) and return-to-sport (RTS) rate between modular BKA and TKA in early follow-up.MethodsTwenty-five consecutive modular BKA cases with a minimum 2-year follow-up were matched with 50 TKA cases at 1:2 ratio. Demographic data and preoperative functional scores, including the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Knee Society Scores (KSSs), were analyzed to ensure comparability. Postoperative WOMAC score, KSS, range of motion (ROM), Forgotten Joint Score-12 (FJS-12), and RTS rates were compared. Operative time and blood loss were also analyzed.ResultsSignificant differences in the WOMAC-function (median 97.1 vs. 89.7, p < 0.001) and KSS-function (median 90.0 vs. 80.0, p = 0.003) scores were identified between the BKA and TKA groups. ROM was significantly greater in the BKA group than in the TKA group (median 125.0° vs. 120.0°, p = 0.004), in addition to the FJS-12 (median 89.6 vs. 53.1, p < 0.001). The overall RTS rate was significantly higher in the BKA group than in the TKA group (71.6% vs. 56.5%, p = 0.039). Operative time was significantly longer in the BKA group than in the TKA group (median 105.0 vs. 67.5 min, p < 0.001), but blood loss was similar (median 557.6 vs. 450.7 ml, p = 0.334).ConclusionModular BKA demonstrated better functional recovery, better joint perception, and higher RTS rate than TKA; thus, modular BKA can be a good alternative for bicompartmental OA

Correlation between tibial valgus deformity and aspect ratio of resected tibial surface in female Chinese patients undergoing total knee arthroplasty

BackgroundMorphology of the resected tibial surface is the reference for tibial component design, selection, and implantation in total knee arthroplasty (TKA). This comparative study sought to answer whether valgus deformity of the tibia would affect the morphology of the resected tibial surface in TKA.MethodsThirty-one female Chinese patients with valgus tibias were retrospectively and consecutively identified from a single-center registration database. Thirty-one patients with well-aligned tibias were matched in terms of gender, height, and weight. Weight-bearing full-length radiographs and computed tomography images of the whole lower limb were obtained for every case. Tibial resection was mimicked perpendicular to the mechanical axis of the tibia in the frontal plane with 3° of posterior slope and a cut level individualized by the actual intraoperative cut. On the resected surface, mediolateral dimension (MLD), medial anteroposterior dimensions (mAPD), and lateral anteroposterior dimensions (lAPD) were measured, and aspect ratios (AR) were calculated. We compared the AR between the two groups.ResultsThe aspect ratio of resected tibial surface positively correlated with tibial valgus alignment. Patients with valgus tibias had significantly smaller AR (MLD/mAPD) for the medial plateau (1.50 ± 0.06 vs. 1.54 ± 0.07, P = 0.032). However, the AR for the lateral plateau was similar between the two groups (1.63 ± 0.08 vs. 1.65 ± 0.07, P = 0.328).ConclusionThis difference in morphology of resected tibial surface between valgus and well-aligned tibias should be considered in tibial component design, as well as in the selection and placement of TKA implants for knees with valgus tibias

Midterm Survivorship and Complications of Total Knee Arthroplasty in Patients with Dwarfism

Background Dwarfism is associated with skeletal dysplasias and joint deformities that frequently result in osteoarthritis requiring treatment with total knee arthroplasty (TKA). These surgeries can be challenging because of alignment deformities, poor bone stock, and smaller components. This study aims to compare TKA implant survivorship and complications between dwarf and nondwarf patients. Methods A retrospective case-control study was performed from 1997-2014 evaluating 115 TKAs in patients under the height threshold of 147.32 cm. This cohort was compared with 164 patients of normal height. Medical records were reviewed for demographics, surgical characteristics, and outcomes. All cases had 2-year minimum follow-up. Results The revision rate was 8.7% in dwarfs compared with 3.7% in controls (P = .08). The 2-, 5-, and 10-year implant survivorship in dwarfs was 96.4%, 92.5%, and 90.2%, respectively; and 96.6%, 95.6%, and 94.8% for controls, respectively (P = .24). Dwarfs underwent significantly more manipulations for arthrofibrosis (P = .002). There was greater femoral (17.4% vs 2.1%, P < .01) and tibial (6.5% vs 2.7%, P < .01) component overhang in dwarfs compared with controls. Conclusion Despite a 2-fold increase in the revision rate of the dwarf cohort, the midterm survivorship is comparable between the dwarf and nondwarf patients. However, dwarfs were more likely to become stiff and undergo manipulation; the increased propensity for stiffness may be associated with oversized components, as evidenced by greater component overhang. Surgeons should be aware of this increased risk and may consider using smaller or customized implants to account for the morphological differences in this patient population

Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework

BackgroundBladder cancer (BLCA) is the most common malignancy of the urinary tract. On the other hand, disulfidptosis, a mechanism of disulfide stress-induced cell death, is closely associated with tumorigenesis and progression. Here, we investigated the impact of disulfidptosis-related genes (DRGs) on the prognosis of BLCA, identified various DRG clusters, and developed a risk model to assess patient prognosis, immunological profile, and treatment response.MethodsThe expression and mutational characteristics of four DRGs were first analyzed in bulk RNA-Seq and single-cell RNA sequencing data, IHC staining identified the role of DRGs in BLCA progression, and two DRG clusters were identified by consensus clustering. Using the differentially expressed genes (DEGs) from these two clusters, we transformed ten machine learning algorithms into more than 80 combinations and finally selected the best algorithm to construct a disulfidptosis-related prognostic signature (DRPS). We based this selection on the mean C-index of three BLCA cohorts. Furthermore, we explored the differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between high and low-risk groups. To visually depict the clinical value of DRPS, we employed nomograms. Additionally, we verified whether DRPS predicts response to immunotherapy in BLCA patients by utilizing the Tumour Immune Dysfunction and Rejection (TIDE) and IMvigor 210 cohorts.ResultsIn the integrated cohort, we identified several DRG clusters and DRG gene clusters that differed significantly in overall survival (OS) and tumor microenvironment. After the integration of clinicopathological features, DRPS showed robust predictive power. Based on the median risk score associated with disulfidptosis, BLCA patients were divided into low-risk (LR) and high-risk (HR) groups, with patients in the LR group having a better prognosis, a higher tumor mutational load and being more sensitive to immunotherapy and chemotherapy.ConclusionOur study, therefore, provides a valuable tool to further guide clinical management and tailor the treatment of BLCA patients, offering new insights into individualized treatment

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis

China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.This work was supported by National Natural Science Foundation of China (No.30571409), Educational and scientific research program for young and middle-aged instructor of Fujian province (No.JAT160161) and the earmarked fund for Modern Agro-industry Technology Research System (No.CARS-45-KXJ3

Distinct Topological Surface States on the Two Terminations of MnBi4_4Te7_7

The recent discovered intrinsic magnetic topological insulator MnBi2Te4 have been met with unusual success in hosting emergent phenomena such as the quantum anomalous Hall effect and the axion insulator states. However, the surface-bulk correspondence of the Mn-Bi-Te family, composed by the superlattice-like MnBi2Te4/(Bi2Te3)n (n = 0, 1, 2, 3 ...) layered structure, remains intriguing but elusive. Here, by using scanning tunneling microscopy (STM) and angle-resolved photoemission spectroscopy (ARPES) techniques, we unambiguously assign the two distinct surface states of MnBi4Te7 (n = 1) to the quintuple-layer (QL) Bi2Te3 termination and the septuple-layer (SL) MnBi2Te4 termination, respectively. A comparison of the experimental observations with theoretical calculations reveals the diverging topological behaviors, especially the hybridization effect between magnetic and nonmagnetic layers, on the two terminations: a gap on the QL termination originating from the topological surface states of the QL hybridizing with the bands of the beneath SL, and a gapless Dirac-cone band structure on the SL termination with time-reversal symmetry. The quasi-particle interference patterns further confirm the topological nature of the surface states for both terminations, continuing far above the Fermi energy. The QL termination carries a spin-helical Dirac state with hexagonal warping, while at the SL termination, a strongly canted helical state from the surface lies between a pair of Rashba-split states from its neighboring layer. Our work elucidates an unprecedented hybridization effect between the building blocks of the topological surface states, and also reveals the termination-dependent time-reversal symmetry breaking in a magnetic topological insulator, rendering an ideal platform to realize the half-integer quantum Hall effect and relevant quantum phenomena.Comment: 22 Pages, 4 Figure