Effects of supplementing Holstein cows with soybean oil compared with palmitic acid-enriched triglycerides on milk production and nutrient partitioning

Both insulin and trans-10,cis-12 C18:2 (t10c12CLA) can be increased by high-starch diets; thus, it is difficult to determine whether insulin or t10c12CLA mediates nutrient partitioning toward body tissues during milk fat depression. To minimize insulin secretion while manipulating t10c12CLA levels, diets supplemented with palmitic acid-enriched triglycerides and soybean oil were fed to cows. Thirty-two Holstein cows (93 ± 35 d in milk) were included in the crossover experiment with each treatment period being 28 d. Treatment diets contained 25% neutral detergent fiber, 32% starch, 18% crude protein, and 4.6% fatty acids (dry matter basis). Treatment diets contained either palmitic acid-enriched triglycerides (2.5% dry matter, BergaFat T-300, Berg + Schmidt America LLC, Libertyville, IL; PAT) or soybean oil (2.5% dry matter; SBO). Cows were blocked by milk yield, body weight, and parity, and then randomly assigned to 1 of 2 treatment sequences (PAT-SBO or SBO-PAT). Cows fed PAT produced milk with only 3.1% fat, indicating milk fat depression; SBO decreased fat content further to only 2.4%. No effect of treatment was observed on dry matter intake, apparent net energy intake, milk yield, body condition score, or fat thickness over the rump and rib. However, compared with PAT, SBO decreased fat-corrected milk yield, energy-corrected milk yield, milk fat yield, de novo fatty acids, and 16-carbon fatty acid yield, whereas SBO increased body weight gain. Neutral detergent fiber digestibility tended to be lower in SBO, whereas fatty acid digestibility was higher. Additionally, the concentration of plasma insulin, nonesterified fatty acids, and triglycerides, and milk metabolites (trans-10 C18:1 and t10c12CLA) were all higher in SBO. In conclusion, with similar dietary starch content, the diet containing palmitic acid-enriched triglycerides partitioned more energy toward milk synthesis, whereas the diet containing soybean oil partitioned more energy toward body tissue gain.

Acetic Acid Promoted Direct Iodination of Terminal Alkynes with N-Iodosuccinimide: Efficient Preparation of 1-Iodoalkynes

An efficient and highly chemoselective approach for the direct iodination of terminal alkynes using acetic acid as N-iodosuccinimide activated reagent under metal-free conditions has been developed. This facile process tolerates a variety of terminal alkynes and provides the desired products in good to excellent yields (up to 99%).

Crystal structure of 1,1′-bis(diphenylphosphino)ferrocene-(1,1′-bis(diphenylphosphino)ferrocene-κ2 P,P′)-(O-isobutyl sulfurodithioito-κ2 S,S′)copper(I), C39H37CuFeOP2S2

C39H37CuFeOP2S2, triclinic, P1̄ (no. 2), a = 9.6132(10) Å, b = 11.5667(12) Å, c = 16.8739(18) Å, α = 99.732(2)°, β = 96.342(2)°, γ = 93.446(2)°, V = 1832.0(3) Å3, Z = 2, R gt(F) = 0.0455, wR ref(F 2) = 0.1212, T = 293.0 K.

Crystal structure of bis(2,3-diphenyltetrazolidine-5-thione-κ1 S)-(nitrato-κ1 O)-(nitrato-κ2 O,O′)lead(II), C26H20N10O6S2Pb

C26H20N10O6S2Pb, triclinic, P1̄ (no. 2), a = 9.3480(19) Å, b = 12.985(3) Å, c = 14.278(3) Å, α = 113.14(3)°, β = 92.05(3)°, γ = 102.75(3)°, V = 1539.8(7) Å3, Z = 2, R gt(F) = 0.0336, wR ref(F 2) = 0.0874, T = 293.0 K.

Crystal structure of dichloro-bis-(1-butyl-1H-benzo[d]imidazole)-nickel(II), C22H28Cl2N4Ni

C22H28Cl2N4Ni, monoclinic, P21/c (no. 14), a = 9.7332(19) Å, b = 14.886(3) Å, c = 18.623(5) Å, β = 117.45(2)°, V = 2394.5(10) Å3, Z = 4, R gt(F) = 0.0450, wR ref(F 2) = 0.1466, T = 293.0 K.

Crystal structure of bis(N,2-bis(4-ethoxybenzylidene)hydrazine-1-carbohydrazonothioato-κ2 N,S)nickel(II) — N,N-dimethylformamide (1/2), C44H56N10S2O6Ni

C44H56N10S2O6Ni, triclinic, P1̄ (no. 2), a = 9.3077(14) Å, b = 9.9624(14) Å, c = 14.0449(19) Å, α = 70.889(3)°, β = 75.532(2)°, γ = 87.544(3)°, V = 1190.5(3) Å3, Z = 1, R gt(F) = 0.0528, wR ref(F 2) = 0.1279, T = 293 K.

Crystal structure of diisopropyl 2,5-dihydroxycyclohexa-1,4-diene-1,4-dicarboxylate, C14H20O6

C14H20O6, triclinic, P1̄ (no. 2), a = 6.4270(13) Å, b = 8.3458(17) Å, c = 8.4120(17) Å, α = 107.08(3)°, β = 106.43(3)°, γ = 107.37(3)°, V = 376.2(2) Å3, Z = 1, R gt(F) = 0.0521, wR ref(F 2) = 0.1541, T = 294.0 K.

Crystal structure of diisobutyl 2,5-dihydroxycyclohexa-1,4-diene-1,4-dicarboxylate, C16H24O6

C16H24O6, triclinic, P1̄ (no. 2), a = 6.3410(13) Å, b = 7.3430(15) Å, c = 10.241(2) Å, α = 94.06(3)°, β = 103.89(3)°, γ = 113.13(3)°, V = 418.3(8) Å3, Z = 1, R gt(F) = 0.0546, wR ref(F 2) = 0.1691, T = 295(3) K.

SCNrank: spectral clustering for network-based ranking to reveal potential drug targets and its application in pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic malignancy. Due to its wide heterogeneity, PDAC acts aggressively and responds poorly to most chemotherapies, causing an urgent need for the development of new therapeutic strategies. Cell lines have been used as the foundation for drug development and disease modeling. CRISPR-Cas9 plays a key role in every step-in drug discovery: from target identification and validation to preclinical cancer cell testing. Using cell-line models and CRISPR-Cas9 technology together make drug target prediction feasible. However, there is still a large gap between predicted results and actionable targets in real tumors. Biological network models provide great modus to mimic genetic interactions in real biological systems, which can benefit gene perturbation studies and potential target identification for treating PDAC. Nevertheless, building a network model that takes cell-line data and CRISPR-Cas9 data as input to accurately predict potential targets that will respond well on real tissue remains unsolved.

Methods

We developed a novel algorithm ‘Spectral Clustering for Network-based target Ranking’ (SCNrank) that systematically integrates three types of data: expression profiles from tumor tissue, normal tissue and cell-line PDAC; protein-protein interaction network (PPI); and CRISPR-Cas9 data to prioritize potential drug targets for PDAC. The whole algorithm can be classified into three steps: 1. using STRING PPI network skeleton, SCNrank constructs tissue-specific networks with PDAC tumor and normal pancreas tissues from expression profiles; 2. With the same network skeleton, SCNrank constructs cell-line-specific networks using the cell-line PDAC expression profiles and CRISPR-Cas 9 data from pancreatic cancer cell-lines; 3. SCNrank applies a novel spectral clustering approach to reduce data dimension and generate gene clusters that carry common features from both networks. Finally, SCNrank applies a scoring scheme called ‘Target Influence score’ (TI), which estimates a given target’s influence towards the cluster it belongs to, for scoring and ranking each drug target.

Results

We applied SCNrank to analyze 263 expression profiles, CRPSPR-Cas9 data from 22 different pancreatic cancer cell-lines and the STRING protein-protein interaction (PPI) network. With SCNrank, we successfully constructed an integrated tissue PDAC network and an integrated cell-line PDAC network, both of which contain 4414 selected genes that are overexpressed in tumor tissue samples. After clustering, 4414 genes are distributed into 198 clusters, which include 367 targets of FDA approved drugs. These drug targets are all scored and ranked by their TI scores, which we defined to measure their influence towards the network. We validated top-ranked targets in three aspects: Firstly, mapping them onto the existing clinical drug targets of PDAC to measure the concordance. Secondly, we performed enrichment analysis to these drug targets and the clusters there are within, to reveal functional associations between clusters and PDAC; Thirdly, we performed survival analysis for the top-ranked targets to connect targets with clinical outcomes. Survival analysis reveals that overexpression of three top-ranked genes, PGK1, HMMR and POLE2, significantly increases the risk of death in PDAC patients.

Conclusion

SCNrank is an unbiased algorithm that systematically integrates multiple types of omics data to do potential drug target selection and ranking. SCNrank shows great capability in predicting drug targets for PDAC. Pancreatic cancer-associated gene candidates predicted by our SCNrank approach have the potential to guide genetics-based anti-pancreatic drug discovery.

Relationship of residual feed intake and protein efficiency in lactating cows fed high- or low-protein diets

Our objectives were to determine the repeatability of residual feed intake (RFI) across dietary protein levels and to determine the association between RFI and protein efficiency in lactating cows. Holstein cows (n = 166; 92 primiparous, 74 multiparous) with initial milk yield 41.3 ± 9.8 kg/d were fed diets with high or low protein in peak lactation. Experiments were conducted as crossovers with 2 treatment periods of 28 to 35 d. Production of 69 of the 166 cows (42 primiparous, 27 multiparous) was also measured in late lactation. Low-protein diets were 14% crude protein (CP) in peak lactation and 13% CP in late lactation and were formulated to contain adequate rumen-degradable protein to maintain rumen function. High-protein diets were 18% CP in peak lactation and 16% CP in late lactation and contained extra expeller soybean meal to increase absorbed protein. Cows were milked twice daily; DMI and milk yield were recorded daily. Milk composition was measured over 4 consecutive milkings weekly, and body weight (BW) was measured 3 times weekly. Fixed effects of diet, parity, and treatment period, interaction of parity and diet, and random effects of experiment and cow nested within experiment were included in the model to compare intake and production performance between cows fed different levels of CP. The RFI value was calculated for each cow on each treatment based on the actual intake, milk energy output, metabolic BW, and body energy (calculated from BW change and body condition score over the treatment period) change. Ranking of cows for RFI was moderately repeatable across dietary protein in peak lactation (r = 0.59) but less repeatable in late lactation (r = 0.41). Negative correlation was observed between RFI and protein efficiency values (dietary protein captured in milk) for cows in both peak lactation (r = -0.42) and late lactation (r = -0.24), which suggested that cows with higher energy efficiency had greater protein efficiency. In conclusion, RFI was repeatable across dietary protein levels within lactation stage, and cows with lower RFI values utilized protein more efficiently.

Correction to: Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures

The article 'Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures',written by J. A. Kanis, was originally published Online First without Open Access. After publication in volume [#], issue [#] and page [#-#], the author decided to opt for Open Choice and to make the article an Open Access publication.

Crystal structure of dipentyl 2,5-dihydroxycyclohexa-1,4-diene-1,4-dicarboxylate, C18H28O6

C18H28O6, monoclinic, C2/c (no. 15), a = 15.061(3) Å, b = 13.791(3) Å, c = 10.106(2) Å, β = 118.60(3)°, V = 1843.0(8) Å3, Z = 4, R gt(F) = 0.0462, wR ref(F 2) = 0.1315, T = 294.3 K.

Efficient synthesis of 1-iodoalkynes via Al2O3 mediated reaction of terminal alkynes and N-iodosuccinimide

Iodination of terminal alkynes using N-iodosuccinimide (NIS) in the presence of γ-Al₂O₃ was developed to afford 1-iodoalkynes with good to excellent yields (up to 99%). This described approach featured excellent chemoselectivity, good functional group tolerance, and utilization of an inexpensive catalyst.

An efficient Al₂O₃-mediated direct iodination of terminal alkynes was developed to afford 1-iodoalkynes.

A surrogate FRAX model for the Kyrgyz Republic

The hip fracture rates from Kazakhstan were used to create a surrogate FRAX® model for the Kyrgyz Republic.

INTRODUCTION

The International Society for Clinical Densitometry and International Osteoporosis Foundation recommend utilizing a surrogate FRAX model, based on the country-specific risk of death, and fracture data based on a country where fracture rates are considered to be representative of the index country.

OBJECTIVE

This paper describes a surrogate FRAX model for the Kyrgyz Republic.

METHODS

The FRAX model used the incidence of hip fracture from the neighbouring country of Kazakhstan and the death risk for the Kyrgyz Republic.

RESULTS

Compared with the model for Kazakhstan, the surrogate model gave somewhat higher 10-year fracture probabilities for men between 60 and 80 years of age and lower probabilities for men above the age of 80. For women the probabilities were similar up to the age of 75-80 years and then lower. There were very close correlations in fracture probabilities between the surrogate and authentic models (1.00) so that the use of the Kyrgyz model had little impact on the rank order of risk. It was estimated that 2752 hip fractures arose in 2015 in individuals over the age of 50 years in the Kyrgyz Republic, with a predicted increase by 207% to 8435 in 2050.

CONCLUSION

The surrogate FRAX model for the Kyrgyz Republic provides the opportunity to determine fracture probability among the Kyrgyz population and help guide decisions about treatment.

Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures

Guidance is provided in an international setting on the assessment and specific treatment of postmenopausal women at low, high and very high risk of fragility fractures.

INTRODUCTION

The International Osteoporosis Foundation and European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis published guidance for the diagnosis and management of osteoporosis in 2019. This manuscript seeks to apply this in an international setting, taking additional account of further categorisation of increased risk of fracture, which may inform choice of therapeutic approach.

METHODS

Clinical perspective and updated literature search.

RESULTS

The following areas are reviewed: categorisation of fracture risk and general pharmacological management of osteoporosis.

CONCLUSIONS

A platform is provided on which specific guidelines can be developed for national use to characterise fracture risk and direct interventions.

Epidemiology of osteoporotic fracture in Kazakhstan and development of a country specific FRAX model

Retrospective and prospective population-based survey in a region of the Republic of Kazakhstan determined the incidence of fractures at the hip, proximal humerus and distal forearm. The hip fracture rates were used to create a FRAX® model to enhance fracture risk assessment in Kazakhstan.

OBJECTIVE

This paper describes the epidemiology of osteoporotic fractures in the Republic of Kazakhstan that was used to develop a country specific FRAX® tool for fracture prediction.

METHODS

We carried out a retrospective population-based survey in Taldykorgan in the Republic of Kazakhstan representing approximately 1% of the country's population. Hip, forearm and humerus fractures were identified retrospectively in 2015 and 2016 from hospital registers and the trauma centre. Hip fractures were prospectively identified in 2017 from the same sources and additionally from primary care data. Age- and sex-specific incidence of hip fracture and national mortality rates were incorporated into a FRAX model for Kazakhstan. Fracture probabilities were compared with those from neighbouring countries having FRAX models.

RESULTS

The difference in hip fracture incidence between the retrospective and prospective survey indicated that approximately 25% of hip fracture cases did not come to hospital attention. The incidence of hip fracture applied nationally suggested that the estimated number of hip fractures nationwide in persons over the age of 50 years for 2015 was 11,690 and is predicted to increase by 140% to 28,000 in 2050. Hip fracture incidence was a good predictor of forearm and humeral fractures in men but not in women.

CONCLUSION

The FRAX model should enhance accuracy of determining fracture probability among the Kazakh population and help guide decisions about treatment.

Aquaporin4 Knockout Aggravates Early Brain Injury Following Subarachnoid Hemorrhage Through Impairment of the Glymphatic System in Rat Brain

BACKGROUND

It is reported that the expression of aquaporin4 (AQP4) in the brain is increased and leads to the brain edema after subarachnoid hemorrhage (SAH). In this study, by using AQP4 knockout rat model, the opposite role of AQP4 in early brain injury following SAH through modulation of interstitial fluid (ISF) transportation in the brain glymphatic system had been explored.

METHODS

The SAH model was established using endovascular perforation method, the AQP4 knockout rat model was generated using TALENs (transcription activator-like (TAL) effector nucleases) technique. The animals were randomly divided into four groups: sham (n = 16), AQP4^-/-sham (n = 16), SAH (n = 24), and AQP4^-/-SAH groups (n = 27). The roles of AQP4 in the brain water content and neurological function were detected. In addition, immunohistochemistry and Nissl staining were applied to observe the effects of AQP4 on the blood-brain barrier (BBB) integrity and the loss of neurons in the hippocampus. To explore the potential mechanism of these effects, the distribution of Gd-DTPA (interstitial fluid indicator) injected from cisterna magna was evaluated with MRI.

RESULTS

Following SAH, AQP4 knockout could significantly increase the water content in the whole brain and aggravate the neurological deficits. Furthermore, the loss of neuron and BBB disruption in hippocampus were also exacerbated. The MRI results indicated that the ISF transportation in the glymphatic system of AQP4 deficit rat was significantly injured.

CONCLUSION

AQP4 facilitates the ISF transportation in the brain to eliminate the toxic factors; AQP4 knockout will aggravate the early brain injury following SAH through impairment of the glymphatic system.

Crystal structure of Bis(acetato-κ2O,O′)-bis[4-(dimethylamino)pyridine-κN]nickel(II), C18H26N4NiO4

C18H26N4NiO4, triclinic, P1̄ (no. 2), a = 7.7547(16) Å, b = 7.8666(16) Å, c = 8.2798(17) Å, α = 90.46(3)°, β = 96.24(3)°, γ = 93.25(3)°, V = 501.24(18) Å3, Z = 1, Rgt(F) = 0.0294, wRref(F2) = 0.0873, T = 310 K.

Higher thyroid-stimulating hormone levels in the first trimester are associated with gestational diabetes in a Chinese population

AIM

To evaluate the relationship between maternal thyroid-stimulating hormone levels during the first trimester and gestational diabetes risk.

METHODS

In Tianjin, China, 7258 women underwent a thyroid-stimulating hormone screening test within 12 gestational weeks and then had a glucose challenge test at 24-28 weeks of gestational age. The women with a glucose challenge test ≥7.8 mmol/l underwent a 75 g oral glucose tolerance test. Gestational diabetes was diagnosed following International Association of Diabetes and Pregnancy Study Group criteria. Restricted cubic spline analysis was performed to explore full-range risk associations of thyroid-stimulating hormone levels with gestational diabetes. Logistic regression was performed to obtain odds ratios and 95% confidence intervals.

RESULTS

In all, 594 women (8.2%) had gestational diabetes. Among women with thyroid-stimulating hormone ≤3.2 mIU/l, a positive association between thyroid-stimulating hormone levels and gestational diabetes risk was found (adjusted OR: 1.13, 95% CI: 1.00-1.27). There was no relationship between thyroid-stimulating hormone levels and gestational diabetes risk in univariable and multivariable analyses among women with thyroid-stimulating hormone >3.2 mIU/l. In subgroup analyses, among women with thyroid-stimulating hormone ≤3.2 mIU/l and BMI ≥25 kg/m² , the adjusted odds ratio for thyroid-stimulating hormone levels with gestational diabetes was enhanced to 1.25 (95% CI: 1.02-1.53).

CONCLUSIONS

In pregnant Chinese women, thyroid-stimulating hormone levels even within normal range in the first trimester were positively related to gestational diabetes risk, especially for pre-pregnancy overweight/obese women.

Crystal structure of 1-(5-(4-chlorophenyl)-3-(2-fluorophenyl)-4,5-dihydro-1H-pyrazol-1-yl)ethan-1-one, C17H14N2OFCl

C17H14N2OFCl, triclinic, P1̄ (no. 2), a = 8.2387(19) Å, b = 9.764(2) Å, c = 10.644(3) Å, α = 72.023(4)°, β = 72.770(4)°, γ = 78.581(4)°, V = 772.5(3) Å3, Z = 2, Rgt(F) = 0.0444, wRref(F2) = 0.1099, T = 294.15 K.

Psychometric Evaluation of the Neuropsychological Test Battery in Individuals with Normal Cognition, Mild Cognitive Impairment, or Mild to Moderate Alzheimer's Disease: Results from a Longitudinal Study

BACKGROUND

The Neuropsychological Test Battery (NTB) is a combination of widely used clinical neuropsychological tests measuring memory and executive function and was designed to overcome some of the limitations of the traditionally used Alzheimer's disease Assessment Scale - Cognitive subscale (ADAS-Cog). A previously reported account indicated high levels of NTB reliability in patients with mild-to-moderate Alzheimer's disease (AD) and mild cognitive impairment (MCI).

OBJECTIVES

We examined capacity of the Neuropsychological Test Battery (NTB) and its component subtests to measure cognitive change over time. Correlations with other cognitive and functional assessments were also determined. Design, Settings, Participants: This was a multicentre, prospective, non-interventional, longitudinal cohort study involving patients with mild-to-moderate AD (n=196), MCI (n=70), or cognitively normal control participants (NC, n=75).

INTERVENTION

The NTB, as well as other Clinical Outcome Assessments including, ADAS-Cog, other cognitive measures, functional/behavioral questionnaires, health outcome questionnaires, and resource utilization tools were administered.

RESULTS

Mean change from baseline for the NTB composite score and the six individual NTB subtests showed greater reductions in performance over time in the AD and MCI groups, compared with NC group. The ADAS-Cog was found to be more sensitive to change than the NTB in all three populations.

CONCLUSIONS

The NTB showed high correlation with the ADAS-Cog and appears to be a sensitive and reliable assessment tool for measuring cognitive decline in patients with mild-to-moderate AD. However, the ADAS-Cog was found to be more sensitive to change over time in both the AD and MCI populations.