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Enantioselective protonation by hydrophosphinylation of diarylphosphine oxides with 2-vinyl azaheterocycle N-oxide derivatives was demonstrated using chiral bis(guanidino)iminophosphorane as the higher-order organosuperbase catalyst. It was confirmed by several control experiments that a chiral weak conjugate acid of the chiral bis(guanidino)iminophosphorane, instead of achiral diarylphosphine oxides, directly functioned as the proton source to afford the corresponding product in a highly enantioselective manner in most cases. Enantioselective protonation by a weak conjugate acid generated from the higher-order organosuperbase would broaden the scope of enantioselective reaction systems because of utilization of a range of less acidic pronucleophiles. This method is highlighted by the valuable synthesis of a series of chiral P,N-ligands for chiral metal complexes through the reduction of phosphine oxide and N-oxide units of the corresponding product without loss of enantiomeric purity.Radiostereometic analysis (RSA) is a precise method for the functional assessment of joint kinematics. Traditionally, the method is based on tracking of surgically implanted bone markers and analysis is user intensive. We propose an automated method of analysis based on models generated from computed tomography (CT) scans and digitally reconstructed radiographs. The study investigates method agreement between marker-based RSA and the CT bone model-based RSA method for assessment of knee joint kinematics in an experimental setup. Eight cadaveric specimens were prepared with bone markers and bone volume models were generated from CT-scans. Using a mobile fixture setup, dynamic RSA recordings were obtained during a knee flexion exercise in two unique radiographic setups, uniplanar and biplanar. The method agreement between marker-based and CT bone model-based RSA methods was compared using bias and LoA. Results obtained from uniplanar and biplanar recordings were compared and the influence of radiographic setup was considered for clinical relevance. The automated method had a bias of -0.19 mm and 0.11° and LoA within ±0.42 mm and ±0.33° for knee joint translations and rotations, respectively. The model pose estimation of the tibial bone was more precise than the femoral bone. The radiographic setup had no clinically relevant effect on results. In conclusion, the automated CT bone model-based RSA method had a clinical precision comparable to that of marker-based RSA. The automated method is non-invasive, fast, and clinically applicable for functional assessment of knee kinematics and pathomechanics in patients.Primary dysmenorrhea (PDM) is cyclic menstrual pain in the absence of pelvic anomalies, and it is thought to be a sex-hormone related disorder. Existing study has focused on the effects of menstrual cramps on brain function and structure, ignoring the psychological changes associated with menstrual pain. Here we examined whether pain empathy in PDM differs from healthy controls (HC) using task-based functional magnetic resonance imaging (fMRI). Fifty-seven PDM women and 53 matched HC were recruited, and data were collected at the luteal and menstruation phases, respectively. During fMRI scans, participants viewed pictures displaying exposure to painful situations and pictures without any pain cues and assessed the level of pain experienced by the person in the picture. Regarding the main effect of the pain pictures, our results showed that compared to viewing neutral pictures, viewing pain pictures caused significantly higher activation in the anterior insula (AI), anterior cingulate cortex, and the left inferior parietal lobule; and only the right AI exhibited a significant interaction effect (group × picture). Post-hoc analyses confirmed that, relative to neutral pictures, the right AI failed to be activated in PDM women viewing painsss pictures. Additionally, there was no significant interaction effect between the luteal and menstruation phases. It suggests that intermittent pain can lead to abnormal empathy in PDM women, which does not vary with the pain or pain-free phase. Our study may deepen the understanding of the relationship between recurrent spontaneous pain and empathy in a clinical disorder characterized by cyclic episodes of pain.Subjective cognitive decline (SCD) is a high-risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD individuals with two (baseline and 7 years later) neuropsychological evaluations and a baseline T1-weighted structural MRI. A machine learning-based model was trained based on 198 baseline neuroimaging (morphometric) features and a battery of 25 clinical measurements to discriminate 24 progressive SCDs who converted to mild cognitive impairment (MCI) at follow-up from 52 stable SCDs. The SCD progression was satisfactorily predicted with the combined features. A history of stroke, a low education level, a low baseline MoCA score, a shrunk left amygdala, and enlarged white matter at the banks of the right superior temporal sulcus were found to favor the progression. This is to date the largest retrospective study of SCD-to-MCI conversion with the longest follow-up, suggesting predictable far-future cognitive decline for the risky populations with baseline measures only. These findings provide valuable knowledge to the future neuropathological studies of AD in its prodromal phase.A decade ago, de novo transcriptome assembly evolved as a versatile and powerful approach to make evolutionary assumptions, analyse gene expression, and annotate novel transcripts, in particular, for non-model organisms lacking an appropriate reference genome. Various tools have been developed to generate a transcriptome assembly, and even more computational methods depend on the results of these tools for further downstream analyses. In this issue of Molecular Ecology Resources, Freedman et al. Tasquinimod cell line (Mol Ecol Resourc 2020) present a comprehensive analysis of errors in de novo transcriptome assemblies across public data sets and different assembly methods. They focus on two implicit assumptions that are often violated First, the assembly presents an unbiased view of the transcriptome. Second, the expression estimates derived from the assembly are reasonable, albeit noisy, approximations of the relative frequency of expressed transcripts. They show that appropriate filtering can reduce this bias but can also lead to the loss of a reasonable number of highly expressed transcripts.