Free Triiodothyronine Levels are Related to Executive Function and Scene Memory in Type 2 Diabetes Mellitus Patients Without Diagnosed Thyroid Diseases

PURPOSE

We aim to determine the role of free triiodothyronine (FT3), the main active ingredient of thyroid hormones (THs), in type 2 diabetes mellitus (T2DM) patients with mild cognitive impairment (MCI).

PATIENTS AND METHODS

A total of 255 T2DM patients without diagnosed thyroid diseases were recruited and divided into MCI group and healthy cognition group. Neuropsychological functions were observed by multidimensional cognitive function scales in including MoCA, Digit Span Test (DST), Verbal Fluency Test (VFT), Clock drawing test (CDT), Trail Making Test (TMT) A and B, Instantaneously Recalled Auditory Verbal Learning Test (AVLT-IR), Delayed Recalled Auditory Verbal Learning Test (AVLT-DR) and Logical Memory Test (LMT). Correlation and logistic regression analyses were performed to explore the association between FT3 and diabetic cognitive dysfunction.

RESULTS

Compared with 147 normal cognition patients, 108 MCI patients exhibited lower FT3 and higher HOMA-IR. FT3 level was not only positively correlated with MoCA scores, but DST, VFT and LMT, while negatively associated with TMTB. Furthermore, there is a negative association between FT3 and HOMA-IR. Logistic regression showed that decreased FT3 is a risk factor of MCI in T2DM patients. Although FT3 is not the risk factor of MCI after homeostasis model assessment of insulin resistance (HOMA-IR) was entered as an independent variable, lower FT3 is associated with VFT and LMT adjusted by age, education, BMI, DM duration, HBP duration, smoking, HbA1c and HOMA-IR.

CONCLUSION

Lower FT3 levels may involve in MCI, especially for executive function and scene memory in T2DM patients without diagnosed thyroid diseases.

Incorporating structural features to improve the prediction and understanding of pathogenic amino acid substitutions

BACKGROUND

The wide application of gene sequencing has accumulated numerous amino acid substitutions (AAS) with unknown significance, posing significant challenges to predicting and understanding their pathogenicity. While various prediction methods have been proposed, most are sequence-based and lack insights for molecular mechanisms from the perspective of protein structures. Moreover, prediction performance must be improved.

METHODS

Herein, we trained a random forest (RF) prediction model, namely AAS3D-RF, underscoring sequence and three-dimensional (3D) structure-based features to explore the relationship between diseases and AASs.

RESULTS

AAS3D-RF was trained on more than 14,000 AASs with 21 selected features, and obtained accuracy (ACC) between 0.811 and 0.839 and Matthews correlation coefficient (MCC) between 0.591 and 0.684 on two independent testing datasets, superior to seven existing tools. In addition, AAS3D-RF possesses unique structure-based features, context-dependent substitution score (CDSS) and environment-dependent residue contact energy (ERCE), which could be applied to interpret whether pathogenic AASs would introduce incompatibilities to the protein structural microenvironments.

CONCLUSION

AAS3D-RF serves as a valuable tool for both predicting and understanding pathogenic AASs.

Superior High-Temperature Strength in a Supersaturated Refractory High-Entropy Alloy

Refractory high-entropy alloys (RHEAs) show promising applications at high temperatures. However, achieving high strengths at elevated temperatures above 1173K is still challenging due to heat softening. Using intrinsic material characteristics as the alloy-design principles, a single-phase body-centered-cubic (BCC) CrMoNbV RHEA with high-temperature strengths (beyond 1000 MPa at 1273 K) is designed, superior to other reported RHEAs as well as conventional superalloys. The origin of the high-temperature strength is revealed by in situ neutron scattering, transmission-electron microscopy, and first-principles calculations. The CrMoNbV's elevated-temperature strength retention up to 1273 K arises from its large atomic-size and elastic-modulus mismatches, the insensitive temperature dependence of elastic constants, and the dominance of non-screw character dislocations caused by the strong solute pinning, which makes the solid-solution strengthening pronounced. The alloy-design principles and the insights in this study pave the way to design RHEAs with outstanding high-temperature strength.

Gradient cell-structured high-entropy alloy with exceptional strength and ductility

[Figure: see text].

Predicting Mutational Effects on Receptor Binding of the Spike Protein of SARS-CoV-2 Variants

The pandemic caused by SARS-CoV-2 has cost millions of lives and tremendous social/financial loss. The virus continues to evolve and mutate. In particular, the recently emerged "UK", "South Africa", and Delta variants show higher infectivity and spreading speed. Thus, the relationship between the mutations of certain amino acids and the spreading speed of the virus is a problem of great importance. In this respect, understanding the mutational mechanism is crucial for surveillance and prediction of future mutations as well as antibody/vaccine development. In this work, we used a coarse-grained model (that was used previously in predicting the importance of mutations of N501) to calculate the free energy change of various types of single-site or combined-site mutations. This was done for the UK, South Africa, and Delta mutants. We investigated the underlying mechanisms of the binding affinity changes for mutations at different spike protein domains of SARS-CoV-2 and provided the energy basis for the resistance of the E484 mutant to the antibody m396. Other potential mutation sites were also predicted. Furthermore, the in silico predictions were assessed by functional experiments. The results establish that the faster spreading of recently observed mutants is strongly correlated with the binding-affinity enhancement between virus and human receptor as well as with the reduction of the binding to the m396 antibody. Significantly, the current approach offers a way to predict new variants and to assess the effectiveness of different antibodies toward such variants.

Optimal duration of dual antiplatelet therapy followed by monotherapy in diabetic patients after percutaneous coronary intervention with drug‑eluting stent implantation: a Bayesian network meta-analysis

INTRODUCTION

The standard 12-month dual antiplatelet therapy (DAPT) following percutaneous coronary intervention (PCI) with drug-eluting stent (DES) implantation that is recommend for the general population may not be suitable for diabetes patients.

OBJECTIVES

To evaluate the efficacy and safety of short-term (≤3 months), midterm (6 months), standard-term (12 months), and extended-term (>12 months) DAPT in diabetes patients with DES implantation. To compare discontinuation of DAPT followed by monotherapy with aspirin versus P2Y12 inhibitor.

PATIENTS AND METHODS

Randomized controlled trials were searched using PubMed, Web of Science, Embase, Cochrane library, and clinicaltrials.gov up to October 10, 2020. A Bayesian network meta-analysis was conducted with a random-effects model. A total of 18 randomized trials including 20,536 diabetes patients were included.

RESULTS

The network analysis showed that short-term DAPT was the best for reducing the primary endpoint and was superior to extended-term DAPT (odds ratio [OR] 0.48, 95% CI: 0.25-0.85). Standard-term DAPT was also associated with a reduced primary endpoint in comparison with extended-term DAPT (OR 0.56, 95% CI: 0.32-0.90). There was no noticeable difference with respect to the primary endpoint between short-term DAPT followed by aspirin monotherapy and P2Y12 inhibitor monotherapy. No significant differences were observed in secondary endpoints, including all-cause mortality, cardiac mortality, myocardial infarction, stroke, target vessel revascularization, definite or probable stent thrombosis, and major bleeding event.

CONCLUSIONS

Short-term DAPT was associated with better primary endpoint benefit for patients with diabetes after PCI with DES than extended-term DAPT.

Decreased Plasma Level of Lipoprotein Lipase Predicted Verbal Disfluency in Chinese Type 2 Diabetes Mellitus Patients with Early Cognitive Deficits

BACKGROUND

Lipoprotein Lipase (LPL) is the rate-limiting enzyme catalyzing the hydrolysis of triglycerides and contributes to the amyloid-β formation, which shows promise as a pathological factor of cognitive decline in Type 2 Diabetes Mellitus (T2DM). This study aimed to investigate the pathogenetic roles of LPL and rs328 polymorphism in Mild Cognitive Impairment (MCI) in patients with T2DM.

METHODS

Chinese patients with T2DM were recruited and divided into two groups based on the Montreal Cognitive Assessment score. Demographic data were collected, LPL was measured and neuropsychological test results were examined.

RESULTS

Seventy-nine patients with diabetes and MCI had significantly decreased plasma LPL levels (p = 0.007) when compared with health-cognition controls (n = 91). Correlation analysis revealed that LPL was positively correlated with clock drawing test (r = 0.158, p = 0.043) and logical memory test (r = 0.162, p = 0.037), while lipoprotein a (r = -0.214, p = 0.006) was inversely associated with LPL. Logistic regression analysis further demonstrated that LPL concentration was an independent factor for diabetic MCI (p = 0.036). No significant differences were observed in the distributions of rs328 variants between patients with MCI and the controls. Moreover, no remarkable association was found among plasma LPL levels, cognitive performances, and lipid levels between the genotypic subgroups. The trail making test A was increased in the GC group when compared with the CC genotype in the control group.

CONCLUSION

Decreased plasma level of LPL could probably predict early cognitive deficits, especially verbal disfluency.

Inverted U-shaped correlation between serum low-density lipoprotein cholesterol levels and cognitive functions of patients with type 2 diabetes mellitus

BACKGROUND

Low-density lipoprotein cholesterol (LDL-C) metabolic disorder is common in individuals with diabetes. The role of LDL-C in mild cognitive impairment (MCI) remains to be explored. We aim to investigate the associations between LDL-C at different levels and details of cognition decline in patients with type 2 diabetes mellitus (T2DM).

METHODS

Patients with T2DM (n = 497) were recruited. Clinical parameters and neuropsychological tests were compared between patients with MCI and controls. Goodness of fit was assessed to determine the linear or U-shaped relationship between LDL-C and cognitive function. The cut-off point of LDL-C was calculated. Correlation and regression were carried out to explore the relationship between cognitive dysfunction and LDL-C levels above and below the cut-off point.

RESULTS

Although no significant difference in LDL-C levels was detected in 235 patients with MCI, compared with 262 patients without MCI, inverted-U-shaped association was determined between LDL-C and Montreal Cognitive Assessment (MoCA). The cut-off point of LDL-C is 2.686 mmol/l. LDL-C (>2.686 mmol/l) is positively related to Trail Making Test B (TMTB) indicating executive function. LDL-C (<2.686 mmol/l) is positively associated with Clock Drawing Test (CDT) reflecting visual space function in patients with T2DM.

CONCLUSION

Inverted U-shaped correlation was found between serum LDL-C and cognitive function in patients with T2DM. Despite that the mechanisms of different LDL-C levels involved in special cognitive dysfunctions remain incompletely clarified, excessive LDL-C damages executive function, while the deficient LDL-C impairs visual space function.

TRIAL REGISTRATION

ChiCTR-OCC-15006060 .

Comparative efficacy of the bone-anchored maxillary protraction protocols for orthopaedic treatment in skeletal Class III malocclusion: A Bayesian network meta-analysis

OBJECTIVE

To compare the treatment effects of five bone-anchored maxillary protraction protocols (BAC3E, BAMP, BARME-FM, BARME-ME, SAFM) for skeletal Class III malocclusion.

METHODS

We conducted a systematic literature search through CENTRAL, EBSCO, PubMed and Web of Science and included the randomized controlled trials and clinical controlled trials, which met the criteria. A Bayesian network meta-analysis (NMA) for SNA, SNB, ANB, SN-MP and Wits appraisal was performed in R software using a random consistency model. The additional analyses included node-splitting analysis, statistical heterogeneity analysis, sensitivity analysis and ranking probability by SUCRA.

RESULTS

A total of 598 articles were initially obtained; 13 articles involving 482 individuals were eventually included. Among the five bone-anchored maxillary protraction protocols, the largest increment in SNA and Wits appraisal was observed in the BAMP group and BAC3E group, respectively; the SAFM, BAC3E and BAMP groups showed similar capability in terms of changes of ANB; least clockwise rotation of the mandible was found in the BARME-ME group, followed by the BAMP group; dental compensation appears to be most pronounced in the BAC3E group; and intermaxillary traction seems to reduce the lingual inclination of lower incisors and even cause labial inclination.

CONCLUSIONS

The SAFM, BAMP and BAC3E groups seem to be advantageous in the improvement of the maxillo-mandibular relationship, followed by the BARME-FM and BARME-ME groups. The findings of this study should be interpreted with caution as only short-term effects were compared and the quality of evidence ranged from very low to moderate. More RCTs with high-quality and long-term investigation are needed.

On-Surface Bottom-Up Construction of COF Nanoshells towards Photocatalytic H2 Production

The rational design of an outer shell is of great significance to promote the photocatalytic efficiency of core-shell structured photocatalysts. Herein, a covalent organic framework (COF) nanoshell was designed and deposited on the cadmium sulfide (CdS) core surface. A typical COF material, TPPA, featuring exceptional stability, was synthesized through interfacial polymerization using 1, 3, 5-triformylphloroglucinol (TP) and p-phenylenediamine (PA) as monomers. The nanoshell endows the CdS@TPPA nanosphere with ordered channels for unimpeded light-harvesting and fast diffusion of reactants/products and well-defined modular building blocks for spatially charge separation. Moreover, the heterojunction formed between CdS and TPPA can further facilitate the effective charge separation at the interface via lower exciton binding energy compared with that of pristine TPPA. By modulating the thickness of TPPA nanoshell, the CdS@TPPA nanosphere photocatalyst with the nanoshell thickness of about 8 ± 1 nm exhibits the highest photocatalytic H₂ evolution of 194.1 μmol h⁻¹ (24.3 mmol g⁻¹ h⁻¹, 8 mg), which is superior to most of the reported COF-based photocatalysts. The framework nanoshell in this work may stimulate the thinking about how to design advanced shell architecture in the core-shell structured photocatalysts to achieve coordinated charge and molecule transport.

Associations of Plasma BACE1 Level and BACE1 C786G Gene Polymorphism with Cognitive Functions in Patients with Type 2 Diabetes: A Cross- Sectional Study

BACKGROUND

β-Site APP-cleaving enzyme 1 (BACE1) is a key enzyme involved in the pathophysiology of Type 2 Diabetes Mellitus (T2DM) and Mild Cognitive Impairment (MCI). We aimed to investigate the potential associations of plasma BACE1 levels and BACE1 gene polymorphism with different cognitive performances in T2DM patients with MCI.

METHODS

The recruited 186 T2DM subjects were divided into 92 MCI group and 94 healthy-cognition controls, according to the Montreal Cognitive Assessment (MoCA) scores. Sociodemographic characteristics, clinical parameters and neuropsychological tests were assessed. BACE1 C786G gene polymorphism and plasma BACE1 level were determined.

RESULTS

Compared to controls, MCI patients exhibited higher plasma BACE1 levels. Plasma BACE1 levels were negatively associated with MoCA, Clock Drawing Test and Logical Memory Test scores, whereas positively associated with Trail Making Test-B time in the MCI group (all p<0.05), after adjusting fasting blood glucose, glycosylated hemoglobin, and homeostasis model assessment of insulin resistance by C-peptide. Multivariable logistic regression analysis showed a significant trend towards increased MCI risk with high plasma BACE1 level in T2DM patients (OR = 1.492, p = 0.027). The plasma BACE1 levels of GG and GC genotypes were obviously higher than that of CC genotype in T2DM-MCI patients (p = 0.035; p = 0.026, respectively).

CONCLUSION

Increased plasma BACE1 levels were associated with poor overall cognition functions, especially visuospatial abilities, visual/logical memory and executive functions in T2DM-MCI patients. Additionally, elevated plasma BACE1 level was a risk factor for MCI in T2DM patients, and might be influenced by BACE1 C786G gene mutations.

Elevated Plasma Free Fatty Acid Susceptible to Early Cognitive Impairment in Type 2 Diabetes Mellitus

BACKGROUND

Elevated free fatty acid (FFA) induces lipotoxicity, attributed to diabetes and cognitive decline. Sterol regulatory element-binding protein-1c (SREBP-1c) regulates lipid metabolism.

OBJECTIVE

We investigated the roles of FFA in mild cognitive impairment (MCI) of type 2 diabetes mellitus (T2DM) patients and determine its association with rs11868035 polymorphism.

METHODS

We recruited 191 Chinese T2DM patients into two groups through Montreal Cognitive Assessment. Demographic and clinical data were collected, multiple domain cognitive functions were tested, plasma FFA levels were measured through ELISA, and SREBP-1c rs11868035 genotype was detected using the Seqnome method.

RESULTS

In comparison with the healthy-cognition group (n = 128), the MCI group (n = 63) displayed lower glucose control (p = 0.012) and higher plasma FFA level (p = 0.021), which were independent risk factors of MCI in T2DM patients in multivariate regression analysis (OR = 1.270, p = 0.003; OR = 1.005, p = 0.036). Additionally, the plasma FFA levels of MCI patients were positively correlated with Stroop color word test-C time scores (r = 0.303, p = 0.021) and negatively related to apolipoprotein A1 levels (r = -0.311, p = 0.017), which are associated positively with verbal fluency test scores (r = 0.281, p = 0.033). Both scores reflected attention ability and executive function. Moreover, the G allele carriers of rs11868035 showed higher digit span test scores than non-carriers in T2DM patients (p = 0.019) but without correlation with plasma FFA levels.

CONCLUSION

In T2DM, elevated plasma level of FFA, when combined with lower apolipoprotein A1 level portends abnormal cholesterol transport, were susceptible to early cognitive impairment, especially for attention and execution deficits. The G allele of SREBP-1c rs11868035 may be a protective factor for memory.

Glucagon-like peptide-1 attenuated carboxymethyl lysine induced neuronal apoptosis via peroxisome proliferation activated receptor-γ

Backgrounds and aims: The role of peroxisome proliferator activated receptor-γ (PPAR-γ) in neuronal apoptosis remains unclear. We aim to investigate the role of PPAR-γ in glucagon-like peptide-1 (GLP-1) alleviated neuronal apoptosis induced by carboxymethyl-lysine (CML).

Materials and Methods: In vitro, PC12 cells were treated by CML/GLP-1. Moreover. the function of PPAR-γ was blocked by GW9662. In vivo, streptozotocin (STZ) was used to induce diabetic rats with neuronal apoptosis. The cognitive function of rats was observed by Morris water maze. Apoptosis was detected by TUNEL assay. Bcl2, Bax, PPAR-γ and receptor of GLP-1 (GLP-1R) were measured by western blotting or immunofluorescence.

Results: In vitro experiment, CML triggered apoptosis, down-regulated GLP-1R and PPAR-γ. Moreover, GLP-1 not only alleviated the apoptosis, but also increased levels of PPAR-γ. GW9662 abolished the neuroprotective effect of GLP-1 on PC12 cells from apoptosis. Furthermore, GLP-1R promoter sequences were detected in the PPAR-γ antibody pulled mixture. GPL-1 levels decreased, while CML levels increased in diabetic rats, compared with control rats. Additionally, we observed elevated bax, decreased bcl2, GLP-1R and PPAR-γ in diabetic rats.

Conclusions: GLP-1 could attenuate neuronal apoptosis induced by CML. Additionally, PPAR-γ involves in this process.

Evaluation of radical surgical treatment in the management of 58 locally advanced rectal neuroendocrine neoplasms, one multicenter retrospective study

BACKGROUND

Locally advanced rectal neuroendocrine neoplasms (NENs) are rare, and the therapeutic effects of surgery in improving the prognosis have been questioned in previous reports.

MATERIALS AND METHODS

The research included 58 consecutive patients with locally advanced rectal NENs from three Chinese medical centers between 2000 and 2020. All have received radical surgical treatment. The clinicopathological and survival data were collected. Kaplan-Meier methods and a Cox proportional hazards regression model were used to evaluate the prognosis and identify independent prognostic factors.

RESULTS

All patients were followed up for a median period of 36 (2-125) months. Of the 58 patients, 13 (22.4%) had G1 neuroendocrine tumors (NETs), 15 (25.9%) had G2 NETs, 6 (10.3%) had G3 NETs, and the remaining 24 (41.4%) patients had G3 neuroendocrine carcinomas (NECs). The 1-year and 3-year disease-free survival (DFS) rates were 64.5% and 48.8%, respectively. The 1-year and 3-year overall survival (OS) rates were 90.5% and 75.4%, respectively. Univariate analysis demonstrated that tumor differentiation (p = 0.002), gross morphology (p = 0.009), T stage (p = 0.024), and extramural vascular invasion (p = 0.009) were associated with the OS. The subsequent multivariate analysis confirmed that tumor differentiation [hazard ratio (HR) = 6.002, 95% confidence interval (CI): 1.210-29.767, p = 0.028] and gross morphology (HR = 3.438, 95% CI: 1.038-11.382, p = 0.043) were independent prognostic factors affecting the clinical outcomes.

CONCLUSIONS

Rectal NENs are a heterogeneous group of diseases. The survival benefits obtained from surgery vary widely based on the tumor clinicopathological features. Patients with G3 NECs and ulcerative mass are at high risks of poor prognosis.

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

Advanced screening strategies for the design of high-entropy alloys are highly desirable. Here the authors use the project-oriented design strategy and CALPHAD-based high-throughput calculation tool to rapidly screen promising Al-Cr-Fe-Mn-Ti structural HEAs for high-temperature applications.

Enhancing fatigue life by ductile-transformable multicomponent B2 precipitates in a high-entropy alloy

Catastrophic accidents caused by fatigue failures often occur in engineering structures. Thus, a fundamental understanding of cyclic-deformation and fatigue-failure mechanisms is critical for the development of fatigue-resistant structural materials. Here we report a high-entropy alloy with enhanced fatigue life by ductile-transformable multicomponent B2 precipitates. Its cyclic-deformation mechanisms are revealed by real-time in-situ neutron diffraction, transmission-electron microscopy, crystal-plasticity modeling, and Monte-Carlo simulations. Multiple cyclic-deformation mechanisms, including dislocation slips, precipitation strengthening, deformation twinning, and reversible martensitic phase transformation, are observed in the studied high-entropy alloy. Its improved fatigue performance at low strain amplitudes, i.e., the high fatigue-crack-initiation resistance, is attributed to the high elasticity, plastic deformability, and martensitic transformation of the B2-strengthening phase. This study shows that fatigue-resistant alloys can be developed by incorporating strengthening ductile-transformable multicomponent intermetallic phases.

A fundamental understanding of fatigue-failure mechanisms is key to develop robust structural materials. Here the authors report a high entropy alloy with enhanced fatigue life by ductile transformable multicomponent B2 precipitates, as revealed by combined experimental and simulation methods.

Bone mesenchymal stem cells attenuate resiniferatoxin-induced neuralgia via inhibiting TRPA1-PKCδ-P38/MAPK-p-P65 pathway in mice

Treatment of neuropathic pain (NP) resulting from nerve injury is one of the most complicated and challenging in modern practice. Pharmacological treatments for NP are not fully effectively and novel approaches are requisite. Recently, transplantation of bone mesenchymal stem cells (BMSCs) has represented a promising approach for pain relief and neural repair, but how it produces beneficial effects on resiniferatoxin (RTX) induced nerve injury is still unclear. Here, we identified the BMSCs' analgesic effects and their potential mechanisms of microglial cells activation on RTX induced neuralgia. Immunostaining, biochemical studies demonstrated that microglia rather than astrocyte cells activation involved in RTX induced mechanical hyperalgesia, whereas the GFP-labeled BMSCs alleviated this mechanical hyperalgesia. Moreover, pain-related TRPA1, PKCδ, CaMKIIɑ (Calcium/calmodulin dependent protein kinase II), P38/MAPK (mitogen-activated protein kinase), p-P65 activation and expression in the spinal cord were significantly inhibited after BMSC administration. In addition, BMSCs treated RTX mice displayed a lower density of mushroom dendritic spines. Our research suggested that activation of PKCδ-CaMKIIɑ-P38/MAPK-p-P65 pathway and mushroom dendritic spines abnormal increase in the spinal cord is the main mechanism of RTX induced neuropathic pain, and transplant of BMSCs to the damaged nerve may offer promising approach for neuropathic pain.

Computational Studies of the Structural Basis of Human RPS19 Mutations Associated With Diamond-Blackfan Anemia

Diamond-Blackfan Anemia (DBA) is an inherited rare disease characterized with severe pure red cell aplasia, and it is caused by the defective ribosome biogenesis stemming from the impairment of ribosomal proteins. Among all DBA-associated ribosomal proteins, RPS19 affects most patients and carries most DBA mutations. Revealing how these mutations lead to the impairment of RPS19 is highly demanded for understanding the pathogenesis of DBA, but a systematic study is currently lacking. In this work, based on the complex structure of human ribosome, we comprehensively studied the structural basis of DBA mutations of RPS19 by using computational methods. Main structure elements and five conserved surface patches involved in RPS19-18S rRNA interaction were identified. We further revealed that DBA mutations would destabilize RPS19 through disrupting the hydrophobic core or breaking the helix, or perturb the RPS19-18S rRNA interaction through destroying hydrogen bonds, introducing steric hindrance effect, or altering surface electrostatic property at the interface. Moreover, we trained a machine-learning model to predict the pathogenicity of all possible RPS19 mutations. Our work has laid a foundation for revealing the pathogenesis of DBA from the structural perspective.

Increased Plasma Level of 24S-Hydroxycholesterol and Polymorphism of CYP46A1 SNP (rs754203) Are Associated With Mild Cognitive Impairment in Patients With Type 2 Diabetes

Background

Abnormal cholesterol metabolism is common in type 2 diabetes mellitus (T2DM) and causes dementia. Cholesterol 24S-hydroxylase (CYP46A1) converts cholesterol into 24S-hydroxycholesterol (24-OHC) and maintains cholesterol homeostasis in the brain.

Objective

This study aimed to investigate the roles of 24-OHC and the CYP46A1 (rs754203) polymorphism in patients with T2DM and mild cognitive impairment (MCI).

Methods

A total of 193 Chinese patients with T2DM were recruited into two groups according to the Montreal Cognitive Assessment (MoCA). Demographic and clinical data were collected, and neuropsychological tests were conducted. Enzyme-linked immunosorbent assay (ELISA) and Seqnome method were used to detect the concentration of plasma 24-OHC and the CYP46A1 rs754203 genotype, respectively.

Results

Compared with 118 healthy cognition participants, patients with MCI (n = 75) displayed a higher plasma level of 24-OHC and total cholesterol concentration (all p = 0.031), while no correlation was found between them. In the overall diabetes population, the plasma level of 24-OHC was negatively correlated with MoCA (r = −0.150, p = 0.039), and it was further proved to be an independent risk factor of diabetic MCI (OR = 1.848, p = 0.001). Additionally, patients with MCI and the CC genotype of CYP46A1 rs754203 showed the highest plasma level of 24-OHC even though the difference was not statistically significant, and they obtained low scores in both the verbal fluency test and Stroop color and word test A (p = 0.008 and p = 0.029, respectively).

Conclusion

In patients with T2DM, high plasma level of 24-OHC and the CC genotype carrier of CYP46A1 rs754203 may portend a high risk of developing early cognitive impairment, including attention and executive deficits.

Unravelling thermal history during additive manufacturing of martensitic stainless steel

In-situ thermal cycling neutron diffraction experiments were employed to unravel the effect of thermal history on the evolution of phase stability and internal stresses during the additive manufacturing (AM) process. While the fully-reversible martensite-austenite phase transformation was observed in the earlier thermal cycles where heating temperatures were higher than A_f, the subsequent damped thermal cycles exhibited irreversible phase transformation forming reverted austenite. With increasing number of thermal cycles, the thermal stability of the retained austenite increased, which decreased the coefficient of thermal expansion. However, martensite revealed higher compressive residual stresses and lower dislocation density, indicating inhomogeneous distributions of the residual stresses and microstructures on the inside and on the surface of the AM component. The compressive residual stresses that acted on the martensite resulted preferentially from transformation strain and additionally from thermal misfit strain, and the decrease in the dislocation density might have been due to the strong recovery effect near the Ac₁ temperature.

IDRMutPred: predicting disease-associated germline nonsynonymous single nucleotide variants (nsSNVs) in intrinsically disordered regions

Motivation

Despite of the lack of folded structure, intrinsically disordered regions (IDRs) of proteins play versatile roles in various biological processes, and many nonsynonymous single nucleotide variants (nsSNVs) in IDRs are associated with human diseases. The continuous accumulation of nsSNVs resulted from the wide application of NGS has driven the development of disease-association prediction methods for decades. However, their performance on nsSNVs in IDRs remains inferior, possibly due to the domination of nsSNVs from structured regions in training data. Therefore, it is highly demanding to build a disease-association predictor specifically for nsSNVs in IDRs with better performance.

Results

We present IDRMutPred, a machine learning-based tool specifically for predicting disease-associated germline nsSNVs in IDRs. Based on 17 selected optimal features that are extracted from sequence alignments, protein annotations, hydrophobicity indices and disorder scores, IDRMutPred was trained using three ensemble learning algorithms on the training dataset containing only IDR nsSNVs. The evaluation on the two testing datasets shows that all the three prediction models outperform 17 other popular general predictors significantly, achieving the ACC between 0.856 and 0.868 and MCC between 0.713 and 0.737. IDRMutPred will prioritize disease-associated IDR germline nsSNVs more reliably than general predictors.

Availability and implementation

The software is freely available at http://www.wdspdb.com/IDRMutPred.

Supplementary information

Supplementary data are available at Bioinformatics online.