Investigation of Antibody Tolerance in Methanol for Analytical Purposes: Methanol Effect Patterns and Molecular Mechanisms.

The extraction of targets from biological samples for immunoassays using organic solvents, such as methanol, is often necessary. However, high concentrations of organic solvents in extracts invariably lead to instability of the employed antibody, resulting in poor performance of the immunoassay. Evaluating the tolerance ability and exploring the molecular mechanisms of antibody tolerance in organic solvents are essential for the development of robust immunoassays. In this work, 25 monoclonal antibodies and methanol are utilized as models to address these questions. A novel protocol is initially established to precisely and rapidly determine antibody tolerance in methanol, identifying two distinct methanol effect patterns. Through a detailed investigation of the structural basis, a novel hypothesis regarding methanol effect patterns is proposed, termed "folding-aggregation," which is subsequently validated through molecular dynamics simulations. Furthermore, the investigation of sequence basis reveals significant differences in residue types within the complementarity-determining regions and ligand-binding residues, distinguishing the two antibody methanol effect patterns. Moreover, the methanol effect patterns of the antibodies are defined by germline antibodies. This work represents the first exploration of antibody methanol effect patterns and associated molecular mechanisms, with potential implications for the discovery and engineering of tolerant antibodies for the development of robust immunoassays.

A two-center study of a combined nomogram based on mammography and MRI to predict ALN metastasis in breast cancer.

OBJECTIVES: To develop and validate a predictive method for axillary lymph node (ALN) metastasis of breast cancer by using radiomics based on mammography and MRI. MATERIALS AND METHODS: A retrospective analysis of 492 women from center 1 (The affiliated Hospital of Qingdao University) and center 2 (Yantai Yuhuangding Hospital) with primary breast cancer from August 2013 to May 2021 was carried out. The radscore was calculated using the features screened based on preoperative mammography and MRI from the training cohort of Center 1 (n = 231), then tested in the validation cohort (n = 99), an internal test cohort (n = 90) from Center 1, and an external test cohort (n = 72) from Center 2. Univariate and multivariate analyses were used to screen for the clinical and radiological characteristics most associated with ALN metastasis. A combined nomogram was established in combination with radscore that predicted the clinicopathological and radiological characteristics. Calibration curves were used to test the effectiveness of the combined nomogram. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the combined nomogram and then compare with the clinical and radiomic models. The decision curve analysis (DCA) value was used to evaluate the combined nomogram for clinical applications. RESULTS: The constructed combined nomogram incorporating the radscore and MRI-reported ALN metastasis status exhibited good calibration and outperformed the radiomics signatures in predicting ALN metastasis (area under the curve [AUC]: 0.886 vs. 0.846 in the training cohort; 0.826 vs. 0.762 in the validation cohort; 0.925 vs. 0.899 in the internal test cohort; and 0.902 vs. 0.793 in the external test cohort). The combination nomogram achieved a higher AUC in the training cohort (0.886 vs. 0.786) and the internal test cohort (0.925 vs. 0.780) and similar AUCs in the validation (0.826 vs. 0.811) and external test (0.902 vs. 0.837) cohorts than the clinical model. CONCLUSION: A combined nomogram based on mammography and MRI can be used for preoperative prediction of ALN metastasis in primary breast cancer.

DDX5 inhibits inflammation by modulating m6A levels of TLR2/4 transcripts during bacterial infection.

DExD/H-box helicases are crucial regulators of RNA metabolism and antiviral innate immune responses; however, their role in bacteria-induced inflammation remains unclear. Here, we report that DDX5 interacts with METTL3 and METTL14 to form an m6A writing complex, which adds N6-methyladenosine to transcripts of toll-like receptor (TLR) 2 and TLR4, promoting their decay via YTHDF2-mediated RNA degradation, resulting in reduced expression of TLR2/4. Upon bacterial infection, DDX5 is recruited to Hrd1 at the endoplasmic reticulum in an MyD88-dependent manner and is degraded by the ubiquitin-proteasome pathway. This process disrupts the DDX5 m6A writing complex and halts m6A modification as well as degradation of TLR2/4 mRNAs, thereby promoting the expression of TLR2 and TLR4 and downstream NF-κB activation. The role of DDX5 in regulating inflammation is also validated in vivo, as DDX5- and METTL3-KO mice exhibit enhanced expression of inflammatory cytokines. Our findings show that DDX5 acts as a molecular switch to regulate inflammation during bacterial infection and shed light on mechanisms of quiescent inflammation during homeostasis.

Prediction of Disease-Free Survival in Breast Cancer using Deep Learning with Ultrasound and Mammography: A Multicenter Study.

BACKGROUND: Breast cancer is a leading cause of cancer morbility and mortality in women. The possibility of overtreatment or inappropriate treatment exists, and methods for evaluating prognosis need to be improved. MATERIALS AND METHODS: Patients (from January 2013 to December 2018) were recruited and divided into a training group and a testing group. All patients were followed for more than 3 years. Patients were divided into a disease-free group and a recurrence group based on follow up results at 3 years. Ultrasound (US) and mammography (MG) images were collected to establish deep learning models (DLMs) using ResNet50. Clinical data, MG, and US characteristics were collected to select independent prognostic factors using a cox proportional hazards model to establish a clinical model. DLM and independent prognostic factors were combined to establish a combined model. RESULTS: In total, 1242 patients were included. Independent prognostic factors included age, neoadjuvant chemotherapy, HER2, orientation, blood flow, dubious calcification, and size. We established 5 models: the US DLM, MG DLM, US + MG DLM, clinical and combined model. The combined model using US images, MG images, and pathological, clinical, and radiographic characteristics had the highest predictive performance (AUC = 0.882 in the training group, AUC = 0.739 in the testing group). CONCLUSION: DLMs based on the combination of US, MG, and clinical data have potential as predictive tools for breast cancer prognosis.

The Application of Three-Dimensional-Printed Hydrogels in Bone Tissue Engineering.

Bone defects are a prevalent clinical issue that presents a serious medical challenge. Bone tissue engineering (BTE) has emerged as an effective approach for treating large bone defects. Hydrogels, as hydrophilic three-dimensional polymers, are recognized as suitable material for BTE due to their excellent biocompatibility and degradability. However, the submicron and nanoporous structure of hydrogels limits the survival of osteoblasts, hindering bone tissue regeneration. In recent years, 3D printing technology has attracted appreciable attention. The use of hydrogels as 3D-printed ink facilitates the printing of hydrogels in any desired shape, enabling personalized or more complex requirements. This article provides a systematic review of the latest applications of 3D-printed hydrogels in BTE. These hydrogels serve as a multifunctional platform for the next generation technology in treating bone defects. The advantages and limitations of 3D-printed hydrogels in BTE are discussed, and future research directions are explored. This review can form the basis for future hydrogel design.

Two-dimensional ß-noble-transition-metal chalcogenide: novel highly stable semiconductors with manifold outstanding optoelectronic properties and strong in-plane anisotropy.

In this work, five two-dimensional (2D) noble-transition-metal chalcogenide (NTMC) semiconductors, namely ß-NX (N = Au, Ag; X = S, Se, Te), were designed and predicted by first-principles simulations. Structurally, the monolayer ß-NX materials have good energetic, mechanical, dynamical, and thermal stability. They contain two inequivalent noble-transition-metal atoms in the unit cell, and the N-X bond comprises a partial ionic bond and a partial covalent bond. Regarding the electronic properties, the ß-NX materials are indirect-band-gap semiconductors with appropriate band-gap values. They have tiny electron effective masses. The hole effective masses exhibit significant differences in different directions, indicating strongly anisotropic hole mobility. In addition, the coexistence of linear and square-planar channels means that the diffusion and transport of carriers should be anisotropic. In terms of optical properties, the ß-NX materials show high absorption coefficients. The absorption and reflection characteristics reveal strong anisotropy in different directions. Therefore, the ß-NX materials are indirect-band-gap semiconductors with good stability, high absorption coefficients, and strong mechanical, electronic, transport, and optical anisotropy. In the future, they could have great potential as 2D semiconductors in nano-electronics and nano-optoelectronics.

A Proof-of-Concept Sandwich Enzyme-Linked Immunoassay Development for Small Molecules.

A sandwich immunoassay theoretically exhibits higher sensitivity and specificity compared to a competitive counterpart; however, it is extremely difficult to obtain a pair of antibodies that can bind to a small molecule simultaneously, which is always thought to be a single epitope. In the present study, abamectin (ABM) was selected to prove the effect of hapten design and antibody recognition properties on the development of a sandwich immunoassay for small molecules. First, the epitopes of ABM were roughly located, and epitope distances were determined. Then, two haptens were designed by introducing spacer arms at the C4″-OH and C5-OH of ABM, respectively, aiming to provide the longest epitope distances. A total of seven rabbit polyclonal antibodies (pAbs) and 21 mouse monoclonal antibodies (mAbs) with various recognition properties were obtained. Extensive combinatorial associations of antibody pairs for simultaneously binding to ABM were performed, and only two mAb-mAb pairs were observed to achieve a sandwich immunoassay for ABM with a total success rate of 0.27%. The best mAb pair for sandwich immunoassay was confirmed by surface plasmon resonance, used to develop a sandwich immunoassay, and then evaluated by cross-reactivities and molecular docking with structurally similar analogues and abamectin. Altogether, the study provided a theoretical foundation as well as practical experience and demonstrated the importance of careful hapten design and extensive antibody screening to successfully establish the sandwich immunoassay for small molecules.

A gas-selective Zn-MOF exhibits selective sensing of Fe3+ ions by doping with Tb3.

Here, a new Zn2+ metal organic framework, {[Me2NH2][Zn2(L)(DTZ)]·2DMF·3H2O}n (Zn-MOF), has been synthesized with low-symmetric carboxylic acid ligand 2,6 bis(2',5'-dicarboxyphenyl)pyridine (H4L) as the main ligand and 3,5-diamino-1,2,4-riazole (DTZ) containing an electron-rich N atom as an auxiliary ligand. Because of its high structural stability and adsorption properties, it can be used to efficiently separate CO2/CH4 and C2H2/CH4. In addition, Tb@Zn-MOF was obtained by doping with Tb3+ to partially replace Zn2+. A study of its luminescence sensing performance demonstrated that Tb@Zn-MOF showed intense luminescence properties and can be used for the directional detection of Fe3+ in aqueous solution. Furthermore, PXRD analysis, UV-vis spectroscopy and X-ray photoelectron spectroscopy (XPS) were also used to study possible luminescence sensing mechanisms. The recognition mechanism for Fe3+ ions is believed to be caused by electron transfer.

Enhanced selectivity of transcutaneous spinal cord stimulation by multielectrode configuration.

Objective.Transcutaneous spinal cord stimulation (tSCS) has been gaining momentum as a non-invasive rehabilitation approach to restore movement to paralyzed muscles after spinal cord injury (SCI). However, its low selectivity limits the types of movements that can be enabled and, thus, its potential applications in rehabilitation.Approach.In this cross-over study design, we investigated whether muscle recruitment selectivity of individual muscles could be enhanced by multielectrode configurations of tSCS in 16 neurologically intact individuals. We hypothesized that due to the segmental innervation of lower limb muscles, we could identify muscle-specific optimal stimulation locations that would enable improved recruitment selectivity over conventional tSCS. We elicited leg muscle responses by delivering biphasic pulses of electrical stimulation to the lumbosacral enlargement using conventional and multielectrode tSCS.Results.Analysis of recruitment curve responses confirmed that multielectrode configurations could improve the rostrocaudal and lateral selectivity of tSCS. To investigate whether motor responses elicited by spatially selective tSCS were mediated by posterior root-muscle reflexes, each stimulation event was a paired pulse with a conditioning-test interval of 33.3 ms. Muscle responses to the second stimulation pulse were significantly suppressed, a characteristic of post-activation depression suggesting that spatially selective tSCS recruits proprioceptive fibers that reflexively activate muscle-specific motor neurons in the spinal cord. Moreover, the combination of leg muscle recruitment probability and segmental innervation maps revealed a stereotypical spinal activation map in congruence with each electrode's position.Significance. Improvements in muscle recruitment selectivity could be essential for the effective translation into stimulation protocols that selectively enhance single-joint movements in neurorehabilitation.

Noninvasive prediction of node-positive breast cancer response to presurgical neoadjuvant chemotherapy therapy based on machine learning of axillary lymph node ultrasound.

OBJECTIVES: To explore an optimal model to predict the response of patients with axillary lymph node (ALN) positive breast cancer to neoadjuvant chemotherapy (NAC) with machine learning using clinical and ultrasound-based radiomic features. METHODS: In this study, 1014 patients with ALN-positive breast cancer confirmed by histological examination and received preoperative NAC in the Affiliated Hospital of Qingdao University (QUH) and Qingdao Municipal Hospital (QMH) were included. Finally, 444 participants from QUH were divided into the training cohort (n = 310) and validation cohort (n = 134) based on the date of ultrasound examination. 81 participants from QMH were used to evaluate the external generalizability of our prediction models. A total of 1032 radiomic features of each ALN ultrasound image were extracted and used to establish the prediction models. The clinical model, radiomics model, and radiomics nomogram with clinical factors (RNWCF) were built. The performance of the models was assessed with respect to discrimination and clinical usefulness. RESULTS: Although the radiomics model did not show better predictive efficacy than the clinical model, the RNWCF showed favorable predictive efficacy in the training cohort (AUC, 0.855; 95% CI 0.817-0.893), the validation cohort (AUC, 0.882; 95% CI 0.834-0.928), and the external test cohort (AUC, 0.858; 95% CI 0.782-0.921) compared with the clinical factor model and radiomics model. CONCLUSIONS: The RNWCF, a noninvasive, preoperative prediction tool that incorporates a combination of clinical and radiomics features, showed favorable predictive efficacy for the response of node-positive breast cancer to NAC. Therefore, the RNWCF could serve as a potential noninvasive approach to assist personalized treatment strategies, guide ALN management, avoiding unnecessary ALND.

Enhanced selectivity of transcutaneous spinal cord stimulation by multielectrode configuration.

Objective: Transcutaneous spinal cord stimulation (tSCS) has been gaining momentum as a non-invasive rehabilitation approach to restore movement to paralyzed muscles after spinal cord injury (SCI). However, its low selectivity limits the types of movements that can be enabled and, thus, its potential applications in rehabilitation. Approach: In this cross-over study design, we investigated whether muscle recruitment selectivity of individual muscles could be enhanced by multielectrode configurations of tSCS in 16 neurologically intact individuals. We hypothesized that due to the segmental innervation of lower limb muscles, we could identify muscle-specific optimal stimulation locations that would enable improved recruitment selectivity over conventional tSCS. We elicited leg muscle responses by delivering biphasic pulses of electrical stimulation to the lumbosacral enlargement using conventional and multielectrode tSCS. Results: Analysis of recruitment curve responses confirmed that multielectrode configurations could improve the rostrocaudal and lateral selectivity of tSCS. To investigate whether motor responses elicited by spatially selective tSCS were mediated by posterior root-muscle reflexes, each stimulation event was a paired pulse with a conditioning-test interval of 33.3 ms. Muscle responses to the second stimulation pulse were significantly suppressed, a characteristic of post-activation depression suggesting that spatially selective tSCS recruits proprioceptive fibers that reflexively activate muscle-specific motor neurons in the spinal cord. Moreover, the combination of leg muscle recruitment probability and segmental innervation maps revealed a stereotypical spinal activation map in congruence with each electrode's position. Significance: Improvements in muscle recruitment selectivity could be essential for the effective translation into stimulation protocols that selectively enhance single-joint movements in neurorehabilitation.

Major depressive disorder is correlated with the mitochondrial ND1 T3394C mutation in two Han Chinese families: Two case reports.

BACKGROUND: Major depressive disorder (MDD) is the most frequent reason of disabled people in the world, as reported by the World Health Organization. However, the diagnosis of MDD is mainly based on clinical symptoms. CASE SUMMARY: The clinical, genetic, and molecular characteristics of two Chinese families with MDD are described in this study. There were variable ages of onset and severity in depression among the families. Both Chinese families had a very low pre-valence of MDD. The mitochondrial genomes of these pedigrees were sequenced and indicated a homoplasmic T3394C (Y30H) mutation, with the polymorphism located at a highly conserved tyrosine at position 30 of ND1. The analysis also revealed unique sets of mitochondrial DNA (mtDNA) polymorphisms orig-inating from haplogroups M9a3 and M9a. CONCLUSION: This finding of the T3394C mutation in two unrelated depressed patients provides strong evidence that this mutation may have a part in the etiology of MDD. However, In these two Chinese families having the T3394C mutation, no functional mtDNA mutation was observed. Therefore, T3394C mutations are related with MDD, and the phenotypic manifestation of these mutations may be affected by changes in nuclear genes or environmental factors.

Diet composition and selection of Père David's deer in Hubei Shishou Milu National Nature Reserve, China.

Hubei Shishou Milu National Nature Reserve is an ideal place to restore the wild population of Père David's deer (Elaphurus davidianus). Understanding foraging ecology and diet composition is essential for assessing population development or establishing long-term effective conservation measures for endangered species. However, little is known about the diet composition of Père David's deer and its diet selection mechanism. In this study, we used stable isotope technology to investigate the diet composition of Père David's deer according to various tissues (i.e., fur, muscle, liver, heart, and feces) and seasons, and evaluated the correlation between the nutrient composition of plants and diet composition. Bayesian isotope analysis showed that the autumn and winter diet estimated by fur and fecal samples indicated a diet dominated by C3 grasses (42.7%-57.2%, mean), while the summer diet estimated by muscle and liver samples was dominated by C3 forbs (30.9%-41.6%, mean). The Pearson correlation test indicated that the contribution of winter diet composition reflected by fur and fecal samples was associated with correlations with crude protein (r = .666, p < .01) and soluble sugars (r = .695, p < .01). The results indicated that crude protein and soluble sugars were important factors influencing the winter diet selection of Père David's deer. In the context of the current reintroduction facing many challenges, such as habitat fragmentation, wetland degradation, and human disturbance, comprehensively evaluating the diet selection mechanism of Père David's deer under different resource specificities and temporal changes should be considered in the future.

Minimum Distance Between Two Epitopes in Sandwich Immunoassays for Small Molecules.

The pursuit of the limit between dimensionalities is a scientific goal with high applicability. Sandwich immunoassay, usually based on two antibodies binding two epitopes, is one of the most popular mainstay tools in both academic and industrial fields. Herein, we determined and evaluated the minimum distance of two epitopes in sandwich immunoassays for small molecules. Briefly, nine model analytes comprising two hapten epitopes, that is, melamine (MEL) and p-nitroaniline (NIA), were designed by increasing the linear chain linkers brick by brick. Two groups of monoclonal antibodies (mAbs) were produced with different recognition properties toward MEL and NIA using 12 new haptens with different spacer arms. The results indicated that two epitopes of the analyte with a distance of only 2.4 Å could be simultaneously bound by two mAbs, which is the known limit of epitope distance in sandwich immunoassays thus far. We further found that an epitope distance of below 8.8 Å for the analyte generally induces noticeable steric hindrance of antibodies, preventing a sandwich immunoassay with high probability. These observations were investigated and evaluated by molecular docking, molecular dynamics, and surface plasmon resonance and using model and real analytes. Altogether, we determined the minimum distance of two epitopes and explored the molecular mechanism of the antibody-analyte-antibody ternary complex in sandwich immunoassays, providing a theoretical basis for hapten design, antibody discovery and development, and sandwich immunoassay establishment for small molecules.

Valuable aramid/cellulose nanofibers derived from recycled resources for reinforcing carbon fiber/phenolic composites.

The scale-up preparation of aramid nanofiber (ANF) and cellulose nanofiber (CNF), still faces serious challenges such as extreme production cost and lengthy preparation cycle. Herein, a feasible top-down strategy was proposed to achieve the efficient reclamation of waste resources, further realizing the large-scale production of high value-added nanofibers. The ANF/CNF as nanoscale building blocks and their reinforcement effects on the mechanical performances of carbon fiber/phenolic composites were investigated. Related strength and modulus of ANF/CNF-enhanced composites in the tensile, bending, shear and nano indentation tests, increased by 118.1% (tensile strength), 141.2% (tensile modulus), 142.2% (flexural strength), 354.4% (flexural modulus), 38.8% (shear strength) and 94.4% (elastic modulus), respectively. Our work offers a valuable reference in the fabrication of low-cost ANF/CNF derived from waste resources, which would facilitate the wide application of nanofibers in fabricating high-performance advanced functional materials.

Metal-organic frameworks/polydopamine synergistic interface enhancement of carbon fiber/phenolic composites for promoting mechanical and tribological performances.

Carbon fiber/phenolic composites have wide application prospects in the transmission of vehicles, where the combination of prominent mechanical and tribological properties is required. Multiscale metal-organic frameworks (MOFs) and polydopamine (PDA) as binary reinforcements were employed to construct a rigid-flexible hierarchical structure for improving the interfacial performances of friction materials. This unique rigid-flexible (MOFs/PDA) reinforcement could act as an effective interfacial linker, significantly facilitating the integration of fibers into the matrix and establishing a strong mechanical interlocking and chemical bonding onto the fiber/matrix interphase, thus boosting the mechanical and tribological properties of the composites. Benefiting from the MOF/PDA synergistic enhancement effects, the interlaminar shear strength of ZIF-8-composites (P1), MOF-5-composites (P2) and UiO-66-(COOH)2-composites (P3) was improved by 70.80%, 43.80% and 53.28%, respectively. In addition, the wear rate of P1 decreased from 3.55 × 10-8 cm3 J-1 to 2.45 × 10-8 cm3 J-1. This work provides a feasible approach for establishing rigid-flexible reinforced structures and opens up a double-component synergistic enhancement strategy to efficiently promote mechanical and tribological properties for fabricating high-performance carbon fiber/phenolic composites.

Breast cancer subtypes affect the ultrasound performance for axillary lymph node status evaluation after neoadjuvant chemotherapy: a retrospective analysis.

PURPOSE: The aim of our study was to investigate the effect of breast cancer subtypes on the diagnostic value of axillary ultrasound for node status evaluation after neoadjuvant chemotherapy. PATIENTS AND METHODS: Pathologic node-positive breast cancer patients underwent axillary ultrasound imaging after neoadjuvant chemotherapy were retrospectively reviewed. The enrolled patients were classified into four subtypes: Luminal A, Luminal B, human epidermal growth factor receptor 2-enriched and triple-negative. Ultrasound images of axillary nodes were reviewed and were evaluated as normal or abnormal and were associated with final pathologic results. Diagnostic value of axillary ultrasound was assessed in four subtypes based on sensitivity, specificity, positive predictive value and negative predictive value. The diagnostic value of axillary ultrasound as well as clinical and pathological characteristics was compared between four breast cancer subtypes using chi-square test or fisher's exact test. RESULT: Luminal A subtype had highest positive predictive value (92.1%), lowest sensitivity (43.8%) and lowest negative predictive value (11.8%). Triple-negative subtype had lowest positive predictive value (73.2%), highest sensitivity (76.9%) and highest negative predictive value (59.1%) (P < 0.05). Luminal B and human epidermal growth factor receptor 2-enriched subtypes had medium sensitivity, positive predictive value and negative predictive value. CONCLUSION: The diagnostic value of axillary ultrasound for node residue disease assessment after neoadjuvant chemotherapy is different between four breast cancer subtypes.

[Characteristics and Factors of Soil Enzyme Activity for Different Plant Communities in Yellow River Delta].

Soil enzymes play key roles in the construction and succession of coastal wetland communities, while the driving mechanism of their activities under water and salt stress conditions is still unclear. The activities and distributions of sucrase, phosphatase, catalase, and urease in the rhizosphere and non-rhizosphere soils of Suaeda salsa, Phragmites australis, and Tamarix chinensis communities were studied in the Yellow River Delta. Moreover, the changes in soil enzyme activities and their influencing factors during the succession of halophytic plant communities were discussed in combination with changes in the physicochemical properties of soil. The results showed significantly higher soil enzyme activities and soil fertility parameters in the rhizosphere soils of S. salsa, P. australis, and T. chinensis communities than those in the non-rhizosphere soils (P<0.05). In the rhizosphere soils, the activities of phosphatase and catalase increased in the order of S. salsa < P. australis < T. chinensis, while they increased in the order of T. chinensis < S. salsa < P. australis for sucrase activity, and S. salsa < T. chinensis < P. australis for urease activity. Further, significant differences were found in the physicochemical properties of rhizosphere soils between different halophyte communities (P<0.05), which indicated that plant types and their rhizosphere effects could affect soil enzyme activities and fertility characteristics. Furthermore, a two-way analysis of variance showed that the rhizosphere effect was greater than that of vegetation type. The soil sucrase activity was significantly positively correlated with available potassium (AK), available phosphorus (AP), and ammonium nitrogen (NH4+-N) (P<0.05). Meanwhile, urease activity was significantly positively correlated with total nitrogen (TN), organic matter (SOM), AK, AP, NH4+-N, and nitrate nitrogen (NO3--N) (P<0.01). Both of the two enzymes were negatively correlated with soil electrical conductivity (EC) (P<0.01). The phosphatase and catalase activities were found to be significantly positively correlated with soil water content (MC), total carbon (TC), TN, total phosphorus (TP), SOM, AK, and NH4+-N (P<0.05). Additionally, parameters of pH, total potassium (TK), and NO3--N were also significantly associated with catalase activity. Finally, the redundancy analysis (RDA) revealed that main factors affecting the overall soil enzyme activity were TC (P<0.01), SOM (P<0.01), MC (P<0.01), TN (P<0.05), NH4+-N (P<0.05), and EC (P<0.05). The findings suggested that soil fertility, water, and salinity are the most influential factors of soil enzyme activity in different halophytic plant communities of the Yellow River Delta.

[Clinical Characteristics of Aldosterone Producing Adenoma and Idiopathic Hyperaldosteronism with Obstructive Sleep Apnea Hypopnea Syndrome].

OBJECTIVE: To investigate the clinical characteristics of aldosterone producing adenoma (APA) and idiopathic hyperaldosteronism (IHA) complicated with obstructive sleep apnea hypopnea syndrome (OSAHS) and the effect of OSAHS on renin-angiotensin-aldosterone system (RAAS) in APA and IHA patients. METHODS: The clinical data of 127 patients with primary aldosteronism (PA) diagnosed from May 2010 to Aug. 2019 were retrospectively analyzed. There were 70 cases of APA, 53 cases of IHA. Another 4 cases were primary adrenal hyperplasia (PAH), so not included into further analysis. According to the results of polysomnography, the 123 patients of APA or IHA were divided into OSAHS group (96 cases) and non-OSAHS group (27 cases ). The patients with OSAHS were divided into mild, moderate and severe subgroups based on apnea hypopnea index (AHI).The clinical characteristics, biochemical parameters, plasma renin activity, aldosterone levels, and the ratio of aldosterone to renin activity (ARR) in the patients of APA and IHA complicated with OSAHS were compared with those of the patients without OSAHS. RESULTS: There were 49 OSAHS cases (49/70, 70.0%) in APA patients. and 47 OSAHS cases (47/53, 88.7%) in IHA patients. The age, male ratio, body mass index (BMI), waist circumference, triglyceride, blood uric acid, and blood creatinine in APA patients with OSAHS were higher than those in APA patients without OSAHS ( P<0.05), while high-density lipoprotein and estimated glomerular filtration rate (eGFR) were lower ( P<0.05). Compared to the patients without OSAHS, IHA-OSAHS patients had higher BMI and waist circumference ( P<0.05). Moderate/severe OSAHS-APA patients exhibited higher plasma renin activity levels and lower ARR values than the APA patients with no/mild OSAHS ( P<0.05). There were no significant differences in plasma renin activity, aldosterone levels, and ARR values between moderate/severe OSAHS-IHA group and no/mild OSAHS-IHA group. CONCLUSION: The prevalence of OSAHS is significantly higher in the patients with PA than normal population, and OSAHS may aggravate glycose, lipid and uric acid metabolism in PA patients. Moderate/severe OSAHS can increase renin levels and decrease ARR values in APA patients, but has no significant effect on RAAS in IHA patients.

Correlation between imaging features and molecular subtypes of breast cancer in young women (≤30 years old).

OBJECTIVES: To analyze the features of digital mammography (DM) plus digital breast tomosynthesis (DBT), ultrasonography (US) and magnetic resonance imaging (MRI) of breast cancer in young women (≤30 years old) and the correlation with molecular subtypes. MATERIALS AND METHODS: We performed a retrospective study of imaging features of consecutive young women aged ≤30 years who were treated and surgically confirmed with breast cancer between January 2013 and December 2019 in our institution. All patients were Chinese women. DM + DBT and US were available for 170 lesions, MRI for 41 lesions. The imaging features were analysed by univariate and multivariate logistic regression analyses to find the predictive factors of the molecular subtypes. RESULTS: The predictive factors of the luminal B(HER2-) subtype (n = 51) were the mass with microcalcifications, irregular shape, spiculated margins, and shadowing posterior features (all P < 0.01). The predictive factors of the luminal B(HER2+) subtype (n = 26) were the spiculated margins (DBT + DM), angular margins (US), shadowing posterior features, and high vascularity (all P < 0.05). The predictive factors of the luminal A subtype (n = 37) were the mass without microcalcifications, spiculated margins, shadowing posterior features, and low vascularity (all P < 0.05). The predictive factors of the triple-negative subtype (n = 31) were the mass without microcalcifications, oval/round shape, circumscribed margins, enhancement of posterior features, and rim enhancement (MRI) (all P < 0.005). The predictive factors of the human-epidermal-growth-factor-receptor-2-enriched subtype (n = 26) were the only microcalcifications, microlobulated margins, and combined posterior feature (all P < 0.05). CONCLUSION: Compared with the general population of breast cancer, this young female population presents a different molecular phenotype distribution. Some imaging features of breast cancer in young women ≤30 years old can be used to predict certain tumor molecular subtypes.