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In CASP15, 87 predictors submitted around 11 000 models on 41 assembly targets. The community demonstrated exceptional performance in overall fold and interface contact predictions, achieving an impressive success rate of 90% (compared to 31% in CASP14). This remarkable accomplishment is largely due to the incorporation of DeepMind's AF2-Multimer approach into custom-built prediction pipelines. To evaluate the added value of participating methods, we compared the community models to the baseline AF2-Multimer predictor. In over 1/3 of cases, the community models were superior to the baseline predictor. The main reasons for this improved performance were the use of custom-built multiple sequence alignments, optimized AF2-Multimer sampling, and the manual assembly of AF2-Multimer-built subcomplexes. The best three groups, in order, are Zheng, Venclovas, and Wallner. Zheng and Venclovas reached a 73.2% success rate over all (41) cases, while Wallner attained 69.4% success rate over 36 cases. Nonetheless, challenges remain in predicting structures with weak evolutionary signals, such as nanobody-antigen, antibody-antigen, and viral complexes. Expectedly, modeling large complexes also remains challenging due to their high memory compute demands. In addition to the assembly category, we assessed the accuracy of modeling interdomain interfaces in the tertiary structure prediction targets. Models on seven targets featuring 17 unique interfaces were analyzed. Best predictors achieved a 76.5% success rate, with the UM-TBM group being the leader. In the interdomain category, we observed that the predictors faced challenges, as in the case of the assembly category, when the evolutionary signal for a given domain pair was weak or the structure was large. Overall, CASP15 witnessed unprecedented improvement in interface modeling, reflecting the AI revolution seen in CASP14.

In CASP14, 39 research groups submitted more than 2500 3D models on 22 protein complexes. In general, the community performed well in predicting the fold of the assemblies (for 80% of the targets), although it faced significant challenges in reproducing the native contacts. This is especially the case for the complexes without whole-assembly templates. The leading predictor, BAKER-experimental, used a methodology combining classical techniques (template-based modeling, protein docking) with deep learning-based contact predictions and a fold-and-dock approach. The Venclovas team achieved the runner-up position with template-based modeling and docking. By analyzing the target interfaces, we showed that the complexes with depleted charged contacts or dominating hydrophobic interactions were the most challenging ones to predict. We also demonstrated that if AlphaFold2 predictions were at hand, the interface prediction challenge could be alleviated for most of the targets. All in all, it is evident that new approaches are needed for the accurate prediction of assemblies, which undoubtedly will expand on the significant improvements in the tertiary structure prediction field.

Background:. Acellular dermal matrices (ADMs) entered the market in the early 2000s and their use has increased thereafter. Several retrospective cohort studies and single surgeon series reported benefits with the use of ADMs. However, robust evidence supporting these advantages is lacking. There is the need to define the role for ADMs in implant-based breast reconstruction (IBBR) after mastectomy. Methods:. A panel of world-renowned breast specialists was convened to evaluate evidence, express personal viewpoints, and establish recommendation for the use of ADMs for subpectoral one-/two-stage IBBR (compared with no ADM use) for adult women undergoing mastectomy for breast cancer treatment or risk reduction using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. Results:. Based on the voting outcome, the following recommendation emerged as a consensus statement: the panel members suggest subpectoral one- or two-stage IBBR either with ADMs or without ADMs for adult women undergoing mastectomy for breast cancer treatment or risk reduction (with very low certainty of evidence). Conclusions:. The systematic review has revealed a very low certainty of evidence for most of the important outcomes in ADM-assisted IBBR and the absence of standard tools for evaluating clinical outcomes. Forty-five percent of panel members expressed a conditional recommendation either in favor of or against the use of ADMs in subpectoral one- or two-stages IBBR for adult women undergoing mastectomy for breast cancer treatment or risk reduction. Future subgroup analyses could help identify relevant clinical and pathological factors to select patients for whom one technique could be preferable to another.

Since the start of COVID‐19 pandemic, a huge effort has been devoted to understanding the Spike (SARS‐CoV‐2)–ACE2 recognition mechanism. To this end, two deep mutational scanning studies traced the impact of all possible mutations across receptor binding domain (RBD) of Spike and catalytic domain of human ACE2. By concentrating on the interface mutations of these experimental data, we benchmarked six commonly used structure‐based binding affinity predictors (FoldX, EvoEF1, MutaBind2, SSIPe, HADDOCK, and UEP). These predictors were selected based on their user‐friendliness, accessibility, and speed. As a result of our benchmarking efforts, we observed that none of the methods could generate a meaningful correlation with the experimental binding data. The best correlation is achieved by FoldX (R = −0.51). When we simplified the prediction problem to a binary classification, that is, whether a mutation is enriching or depleting the binding, we showed that the highest accuracy is achieved by FoldX with a 64% success rate. Surprisingly, on this set, simple energetic scoring functions performed significantly better than the ones using extra evolutionary‐based terms, as in Mutabind and SSIPe. Furthermore, we demonstrated that recent AI approaches, mmCSM‐PPI and TopNetTree, yielded comparable performances to the force field‐based techniques. These observations suggest plenty of room to improve the binding affinity predictors in guessing the variant‐induced binding profile changes of a host–pathogen system, such as Spike–ACE2. To aid such improvements we provide our benchmarking data at https://github.com/CSB-KaracaLab/RBD-ACE2-MutBench with the option to visualize our mutant models at https://rbd-ace2-mutbench.github.io/. [ABSTRACT FROM AUTHOR]

In recent years, emerging two-dimensional (2D) materials, such as molybdenum diselenide (MoSe2), have been at the center of attention for many researchers. This is due to their unique and fascinating physicochemical properties that make them attractive in space and defense applications that include shielding harsh irradiation environments. In this study, we examined the effects of gamma (γ) rays at various doses on the structural, chemical, and optical properties of MoSe2 layers. After the samples were exposed to intense gamma radiation (from a 60Co source) with various exposure times to vary the total accumulated dosage (up to 100 kGy), Raman and photoluminescence spectroscopies were used to study and probe radiation-induced changes to the samples. When compared to pristine materials, very few changes in optical properties were typically observed, indicating good robustness with little sensitivity, even at relatively high doses of gamma radiation. The imaging using scanning electron microscopy revealed a number of nano-hillocks that were connected to substrate alterations. X-ray photoelectron spectroscopies revealed that Mo's binding energies remained the same, but Se's binding energies blueshifted. We associated this shift with the decrease in Se vacancies that occurred after irradiation as a result of Mo atoms creating adatoms next to Se atoms. When compared to pristine materials, very few changes in optical, chemical, and structural properties were typically observed. These findings highlight the inherent resilience of MoSe2 in hostile radioactive conditions, which spurs additional research into their optical, electrical, and structural characteristics as well as exploration for potential space, energy, and defense applications. [ABSTRACT FROM AUTHOR]

Abstract Background The optimum protocol for expander volume adjustment with respect to the timing and application of radiotherapy remains controversial. Methods Eighteen New Zealand rabbits were divided into three groups. Metallic port integrated anatomic breast expanders of 250 cc were implanted on the back of each animal and controlled expansion was performed. Group I underwent radiotherapy with full expanders while in Group II, expanders were partially deflated immediately prior to radiotherapy. Control group did not receive radiotherapy. The changes in blood flow at different volume adjustments were investigated in Group II by laser Doppler flowmetry. Variations in the histopathologic properties of the irradiated tissues including the skin, capsule and the pocket floor, were compared in the biopsy specimens taken from different locations in each group. Results A significant increase in skin blood flow was detected in Group II with partial expander deflation. Overall, histopathologic exam revealed aggravated findings of chronic radiodermatitis (epidermal atrophy, dermal inflammation and fibrosis, neovascularisation and vascular changes as well as increased capsule thickness) especially around the lower expander pole, in Group II. Conclusions Expander deflation immediately prior to radiotherapy, may augment the adverse effects, especially in the lower expander pole, possibly via enhanced radiosensitization due to a relative increase in the blood flow and tissue oxygenation.

The article looks at the self-recovery of the hand, which was explained on the case of a 51-year-old female who had repeated injections of baby oil on her face and hands. The woman suffered from anaphylactic symptoms with inflammation at the injected areas of the face and hands 5 years after the last self-vaccination. She was treated with antihistamines, amateur tattooing to hide the lumps and systemic steroids.