Nomogram based on a circular RNA biomarker for predicting the likelihood of successful sperm retrieval via microdissection testicular sperm extraction in patients with idiopathic non-obstructive azoospermia

BackgroundMany circular RNAs (circRNAs) are specifically expressed in the testes and seminal plasma of patients with non-obstructive azoospermia (NOA), highlighting them as potential predictors of microdissection testicular sperm extraction (micro-TESE) outcomes. Although research has indicated that circular RNA monoglyceride lipase (circ_MGLL) is highly expressed in the testicular tissues of patients with NOA, the association between circ_MGLL expression and sperm retrieval outcomes (SROs) in patients with idiopathic non-obstructive azoospermia (iNOA) receiving micro-TESE remains unclear.MethodsThis single-center, retrospective cohort study enrolled 114 patients with iNOA who underwent micro-TESE at Northwest Women’s and Children’s Hospital from January 2017 to November 2021. A logistic regression model was used to examine associations between SRO and circ_MGLL expression in testicular tissues, the results of which were used in conjunction with previous findings to establish a nomogram. The predictive performance of the circ_MGLL-based nomogram was evaluated via calibration curves, receiver operating characteristic curves, and decision curve analysis (DCA) using an internal validation method.ResultsThe generalized additive model indicated that the probability of successful SRO for micro-TESE decreased as circ_MGLL expression increased in testicular tissues. Across the entire cohort, univariate logistic regression analysis revealed that circ_MGLL expression was inversely associated with SRO in patients with NOA. This trend did not change after stratification according to age, body mass index, testicular volume, follicle-stimulating hormone (FSH) level, luteinizing hormone (LH) level, testosterone (T) level, or pathological type (or after adjusting for these confounders) (odds ratio <1, P < 0.001). A nomogram was then generated by integrating circ_MGLL, pathological types, and FSH, LH, and T levels. The circ_MGLL-based predictive model achieved satisfactory discrimination, with an area under the curve of 0.857, and the calibration curves demonstrated impressive agreement. The DCA indicated that the net clinical benefit of the circ_MGLL-based predictive model was greater than that of circ_MGLL alone.Conclusioncirc_MGLL is significantly associated with the SRO of micro-TESE in patients with iNOA. The circ_MGLL-based nomogram developed in the current study can predict successful SRO with high accuracy

Rapid FRD determination for multiplexed fibre systems -- I. The quasi-near field model and its uncertainties

Focal Ratio Degradation (FRD) in fibres is a crucial factor to control in astronomical instruments in order to minimize light loss. As astronomical instrumentation has advanced, the integration of large populations of fibres has become common. However, determining FRD in multiplexed fibre systems has become a challenging and time-consuming task. The Integral Field Unit for the Fiber Arrayed Solar Optical Telescope (FASOT-IFU) represents the most densely arranged fibre-based IFU in a single unit. Due to the close packing of fibres in the V-groove of the slit end, measuring FRD is particularly challenging as the output spots are prone to overlapping with adjacent fibres. In this paper, a novel method based on the quasi-near field model is proposed to enable rapid FRD measurement in highly multiplexed fibre systems like IFUs and multi-object observation systems. The principle and uncertainties associated with the method are investigated. The method's validity is demonstrated by applying it to determine the FRD in FASOT-IFU, with the achieved FRD performance meeting the acceptable requirements of FASOT-IFU, where the output focal ratio primarily falls within the range of 5.0-7.0. The results indicate that the proposed method offers several advantages, including the simultaneous and rapid measurement of FRD in multiple fibres with high accuracy (error smaller than 0.35 in F-ratio). Furthermore, besides FRD, the method exhibits potential for extensive measurements of throughput, scrambling, and spectral analysis.Comment: 10 pages, 12 figures, submitted to MNRA

Visualization 1.avi

This video provides the real-time results of the in-plane rotation measurement. The playback frame rate is 30 fps. At the top left is the real-time recovered phase map, at the top right is a demonstration of the in-plane rotation (not drawn to scale), and at the bottom is the real-time calculated rotation angle

Exact controllability problem of a wave equation in non-cylindrical domains

Let $\alpha: [0, \infty)\to(0, \infty)$ be a twice continuous differentiable function which satisfies that $\alpha(0)=1$, $\alpha'$ is monotone and $0<c_1\le \alpha'(t)\le c_2<1$ for some constants $c_1$ and $c_2$. The exact controllability of a one-dimensional wave equation in a non-cylindrical domain is proved. This equation characterizes small vibrations of a string with one of its endpoint fixed and the other moving with speed $\alpha'(t)$. By using the Hilbert Uniqueness Method, we obtain the exact controllability results of this equation with Dirichlet boundary control on one endpoint. We also give an estimate on the controllability time that depends only on $c_1$ and $c_2$

Reinforced Pedestrian Attribute Recognition with Group Optimization Reward

Pedestrian Attribute Recognition (PAR) is a challenging task in intelligent video surveillance. Two key challenges in PAR include complex alignment relations between images and attributes, and imbalanced data distribution. Existing approaches usually formulate PAR as a recognition task. Different from them, this paper addresses it as a decision-making task via a reinforcement learning framework. Specifically, PAR is formulated as a Markov decision process (MDP) by designing ingenious states, action space, reward function and state transition. To alleviate the inter-attribute imbalance problem, we apply an Attribute Grouping Strategy (AGS) by dividing all attributes into subgroups according to their region and category information. Then we employ an agent to recognize each group of attributes, which is trained with Deep Q-learning algorithm. We also propose a Group Optimization Reward (GOR) function to alleviate the intra-attribute imbalance problem. Experimental results on the three benchmark datasets of PETA, RAP and PA100K illustrate the effectiveness and competitiveness of the proposed approach and demonstrate that the application of reinforcement learning to PAR is a valuable research direction

Bioactive Diterpenoids from Clerodendrum kiangsiense

A new abeo-abietane diterpenoid, 12-methoxy-6,11,14,16-tetrahydroxy-17(15→16)-abeo-5,8,11,13-abietatetraen-3,7-dione (8), was isolated from the hydroalcoholic extract of the herb of Clerodendrum kiangsiense along with seven known diterpenoids (1–7). Their structures were identified on the basis of spectroscopic analyses including two-dimensional NMR and comparison with literature data. All of these compounds were evaluated for their cytotoxic activities against the growth of human cancer cells lines HL-60, SMMC-7721, A-549 and MCF-7 by the MTT assay. The results showed that cryptojaponol (4), fortunin E (6) and 8 exhibited significant cytotoxicity against four human cancer cell lines

Preparation, Multispectroscopic Characterization, and Stability Analysis of <i>Monascus</i> Red Pigments—Whey Protein Isolate Complex

Monascus red pigments (MRPs) are mainly used as natural food colorants; however, their application is limited due to their poor stability. To expand their areas of application, we investigated the binding constants and capacity of MRPs to whey protein isolate (WPI) and whey protein hydrolysate (WPH) and calculated the surface hydrophobicities of WPI and WPH. MRPs were combined with WPI and WPH at a hydrolysis degree (DH) of 0.5% to form the complexes (DH = 0.0%) and (DH = 0.5%), respectively. Subsequently, the structural characteristics of complex (DH = 0.5%) and WPI were characterized and the color retention rates of both complexes and MRPs were investigated under different pretreatment conditions. The results showed that the maximum binding constant of WPI with MRPs was 0.670 ± 0.06 U−1 and the maximum binding capacity was 180 U/g. Furthermore, the thermal degradation of complex (DH = 0.0%), complex (DH = 0.5%), and MRPs in a water bath at 50–100 °C followed a first-order kinetic model. Thus, the interaction of WPI with MRPs could alter the protein conformation of WPI and effectively protect the stability of MRPs