Solar neighborhoods: the impact of urban layout on a large-scale solar strategies application.

The article addresses the challenges of evaluating energy performance in different neighborhood settings under various energy efficiency measures and proposes a methodology for selecting appropriate solar strategies on a neighborhood scale. The study selects five representative neighborhoods from various climatic zones with different building and street layouts. The proposed methodology involves a systematic three-step multi-domain workflow for implementing energy efficiency measures and solar strategies in the existing neighborhoods. The first step involves typical energy performance simulation, the second step involves energy simulation using high performance building envelope, and the third step involves the addition of solar strategies in combination with retrofitting materials to achieve net-zero status. The results of the study show that modifying the building envelope leads to a significant reduction in energy consumption, with up to 60% reduction observed. The study also finds that the optimal mix of solar strategies depends strongly on the type of neighborhood, its street layouts, and the type of buildings. The article highlights the importance of considering these factors when implementing solar strategies on a neighborhood scale to achieve energy efficiency and net-zero status. It provides urban planners with a systematic decision-making approach to evaluate and optimize neighborhoods to achieve net-zero energy status.

A Comprehensive Investigation of Risk Association Between the -786 T > C, + 884 G > A, VNTR, rs743506, rs3918226 of eNOS and Susceptibility of Migraine: A Updated Meta-Analysis Utilizing Trial Sequential Analysis.

With a feature of complex pathogenic mechanisms, migraine is a well-known common neurovascular disorder. Multiple genes are responsible for hindering the susceptibility of pain threshold one of which is the eNOS gene and its variants. Multiple independent observational studies with case-control design produced conflicting findings, which can be attributed to a variety of factors including varying sample sizes, demographic stratification, technique application, etc. Therefore, in the present study we aimed to find out the precise risk between the selected variant of eNOS and the risk of migraine and its clinical subtypes using a meta-analysis approach. To find the association between the risk variants of the eNOS gene and migraine, a PRISMA-based systematic literature review strategy was utilized to search via online resources including PubMed and Google Scholar. Using several genetic models, odds ratios with 95% confidence intervals were computed to pool the data. To access heterogeneity, Cochran's Q Test and I2 statistics were utilized, while Begg's and Egger's tests were used to determine publication bias. A p-value of 0.05 or below was deemed statistically significant for all two-sided tests. The present meta-analysis was able to find out the significant protective association between rs743506 and migraine after using dominant (OR: 0.66, CI [0.49-0.86]), over-dominant (OR: 0.56, CI [0.42-0.75]), codominant model (OR: 0.58, CI[0.43-0.77]). Only significant risk association was found between rs1799983, rs3918226, and risk of migraine with aura after utilizing recessive and codominant models i.e., HR vs HW and HR vs HT. The present meta-analysis showed that rs743506 showed a protective association in comparison to rs1799983, rs3918226 which showed significant risk in the MA group. Also, TSA showed non-significant results and therefore, in conclusion, more studies are required to establish risk.

Synergistic Inhibitory Effect of Quercetin and Cyanidin-3O-Sophoroside on ABCB1.

The human ABCB1 (P-glycoprotein, Pgp) protein is an active exporter expressed in the plasma membrane of cells forming biological barriers. In accordance with its broad substrate spectrum and tissue expression pattern, it affects the pharmacokinetics of numerous chemotherapeutic drugs and it is involved in unwanted drug-drug interactions leading to side effects or toxicities. When expressed in tumor tissues, it contributes to the development of chemotherapy resistance in malignancies. Therefore, the understanding of the molecular details of the ligand-ABCB1 interactions is of crucial importance. In a previous study, we found that quercetin (QUR) hampers both the transport and ATPase activity of ABCB1, while cyandin-3O-sophroside (C3S) stimulates the ATPase activity and causes only a weak inhibition of substrate transport. In the current study, when QUR and C3S were applied together, both a stronger ATPase inhibition and a robust decrease in substrate transport were observed, supporting their synergistic ABCB1 inhibitory effect. Similar to cyclosporine A, a potent ABCB1 inhibitor, co-treatment with QUR and C3S shifted the conformational equilibrium to the "inward-facing" conformer of ABCB1, as it was detected by the conformation-selective UIC2 mAb. To gain deeper insight into the molecular details of ligand-ABCB1 interactions, molecular docking experiments and MD simulations were also carried out. Our in silico studies support that QUR and C3S can bind simultaneously to ABCB1. The most favourable ligand-ABCB1 interaction is obtained when C3S binds to the central substrate binding site and QUR occupies the "access tunnel". Our results also highlight that the strong ABCB1 inhibitory effect of the combined treatment with QUR and C3S may be exploited in chemotherapy protocols for the treatment of multidrug-resistant tumors or for improving drug delivery through pharmacological barriers.

Deep learning supported machine vision system to precisely automate the wild blueberry harvester header.

An operator of a wild blueberry harvester faces the fatigue of manually adjusting the height of the harvester's head, considering spatial variations in plant height, fruit zone, and field topography affecting fruit yield. For stress-free harvesting of wild blueberries, a deep learning-supported machine vision control system has been developed to detect the fruit height and precisely auto-adjust the header picking teeth rake position. The OpenCV AI Kit (OAK-D) was used with YOLOv4-tiny deep learning model with code developed in Python to solve the challenge of matching fruit heights with the harvester's head position. The system accuracy was statistically evaluated with R2 (coefficient of determination) and σ (standard deviation) measured on the difference in distances between the berries picking teeth and average fruit heights, which were 72, 43% and 2.1, 2.3 cm for the auto and manual head adjustment systems, respectively. This innovative system performed well in weed-free areas but requires further work to operate in weedy sections of the fields. Benefits of using this system include automated control of the harvester's head to match the header picking rake height to the level of the fruit height while reducing the operator's stress by creating safer working environments.

Factors affecting the treatment outcome of injection based shorter MDR-TB regimen at a referral centre in India.

Rifampicin-resistant/multidrug-resistant tuberculosis (RR/MDR-TB) is a significant burden on global tuberculosis (TB) prevention and eradication efforts. MDR-TB can be treated, but it is expensive, takes a long time (typically two years) and contains potentially toxic drugs. Under certain conditions, the WHO recommends standard regimens lasting 9 to 11 months rather than individual regimens lasting at least 18-20 months. The current study sought to identify factors associated with treatment outcomes in RR/MDR-TB patients receiving an injection-based regimen for 9-11 months. This ambispective (prospective and retrospective) observational study was conducted at a tertiary tuberculosis institute in New Delhi, India. Between February 2021 and March 2022, patients with RR/MDR-pulmonary TB who received an injection-based shorter regimen were enrolled. Factors related to treatment outcomes were investigated and compared in patients who had a successful outcome versus those who did not. A total of 55 patients were enrolled, with 50.91% being successful (cured/treatment completed) and 49.09% failing (including failure, lost to follow up, death, and regimen change). The following factors were significantly associated with the unsuccessful outcome, according to univariate analysis: BMI (<18.5 kg/m2), anaemia, previous anti-TB treatment, bilateral chest X-ray involvement, and far advanced disease on chest X-ray. BMI (<18.5 kg/m2), anaemia, and far advanced disease on chest X-ray were all significantly associated with mortality. Anaemia was associated with an unsuccessful outcome (p=0.049) and mortality (p=0.048) in the multiple logistic regression analysis. Early treatment initiation, improved nutrition and anaemia, and regular monitoring can all improve RR/MDR-TB patients' outcomes and prognoses.

LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images.

The syndrome called COVID-19 which was firstly spread in Wuhan, China has already been declared a globally "Pandemic." To stymie the further spread of the virus at an early stage, detection needs to be done. Artificial Intelligence-based deep learning models have gained much popularity in the detection of many diseases within the confines of biomedical sciences. In this paper, a deep neural network-based "LiteCovidNet" model is proposed that detects COVID-19 cases as the binary class (COVID-19, Normal) and the multi-class (COVID-19, Normal, Pneumonia) bifurcated based on chest X-ray images of the infected persons. An accuracy of 100% and 98.82% is achieved for binary and multi-class classification respectively which is competitive performance as compared to the other recent related studies. Hence, our methodology can be used by health professionals to validate the detection of COVID-19 infected patients at an early stage with convenient cost and better accuracy.

The complexities of migraine: A debate among migraine researchers: A review.

Migraine is indeed a neurovascular disorder for which several genes have been identified in this era of Genome-Wide Association Studies (GWAS) and neuroimaging studies have already revealed structural changes and different mechanisms that cause migraine, but the exact cause of this debilitating and disabling neurovascular disorder remained unclear. Low neuronal hyperexcitability ("the migrainous brain") is set and hindered by genetic and environmental factors, respectively. Migraine is also found to be associated with different diseases (co-morbidity). There is still a subject of contention: is migraine a disease of evolution or disease of pathology? This research review seeks to provide a brief overview on the genetics of disorders, structural abnormalities in the brain, CSD-like symptoms, and faulty Trigeminovascular System activation for migraine pain phenotype. This review briefly covered here to provide some ideas that may also be utilized in migraine research and to serve as motivation for future research.

CheXImageNet: a novel architecture for accurate classification of Covid-19 with chest x-ray digital images using deep convolutional neural networks.

Many countries around the world have been influenced by Covid-19 which is a serious virus as it gets transmitted by human communication. Although, its syndrome is quite similar to the ordinary flu. The critical step involved in Covid-19 is the initial screening or testing of the infected patients. As there are no special detection tools, the demand for such diagnostic tools has been increasing continuously. So, it is eminently admissible to find out positive cases of this disease at the earliest so that the spreading of this dangerous virus can be controlled. Although, some methods for the detection of Covid-19 patients are available, which are performed upon respiratory based samples and among them, a critical approach for treatment is radiologic imaging or X-ray imaging. The latest conclusions obtained from X-ray digital imaging based algorithms and techniques recommend that such type of digital images may consist of significant facts regarding the SARS-CoV-2 virus. The utilization of Deep Neural Networks based methodologies clubbed with digital radiological imaging has been proved useful for accurately identifying this disease. This could also be adjuvant in conquering the problem of dearth of competent physicians in far-flung areas. In this paper, a CheXImageNet model has been introduced for detecting Covid-19 disease by using digital images of Chest X-ray with the help of an openly accessible dataset. Experiments for both binary class and multi-class have been performed in this work for benchmarking the effectiveness of the proposed work. An accuracy of 100 % is reported for both binary classification (having cases of Covid-19 and Normal X-Ray) and classification for three classes (including cases of Covid-19, Normal X-Ray and, cases of Pneumonia disease) respectively.

Black fungus immunosuppressive epidemic with Covid-19 associated mucormycosis (zygomycosis): a clinical and diagnostic perspective from India.

The catastrophic phase of Covid-19 turns the table over with the spread of its disastrous transmission network throughout the world. Covid-19 associated with mucormycosis fungal infection accompanied by opportunistic comorbidities have emerged the myriad of complications and manifestations. We searched the electronic databases of Google Scholar, PubMed, Springer, and Elsevier until June 05, 2021, using keywords. We retrieved the details of confirmed and suspected mucormycosis patients associated with Covid-19. We analyzed the case reports, treatment given for Covid-19, steroids used, associated comorbidities, mucormycosis site involved, and patients survived or dead. Overall, 102 patients of mucormycosis associated with Covid-19 have been reported from India. Mucormycosis was predominant in males (69.6%) rather than females (19.6%), and most of the patients were active Covid-19 cases (70.5%). Steroids were mostly used (68.6%) for the treatment of Covid-19 followed by remdesivir (10.7%). Patients were suffering from diabetes mellitus (88.2%) and severe diabetic ketoacidosis (11.7%). Mucormycosis affects the sino-nasal (72.5%), orbit (24.5%), central nervous system (18.6%), and maxillary necrosis (13.7%) of the patients. The Mortality rate was recorded as 23.5%, and recovery rate was 2.9%. Diabetes mellitus cases are highest in India as compared to other countries, and prevalent use of steroids with the background of Covid-19 becomes an opportunistic environment for mucormycosis fungal infection to survive.

Administration of cyclic glycine-proline during infancy improves adult spatial memory, astrocyte plasticity, vascularization and GluR-1 expression in rats.

Cyclic glycine-proline (cGP) is a natural nutrient of breast milk and plays a role in regulating the function of insulin-like growth factor-1 (IGF-1). IGF-1 function is essential for post-natal brain development and adult cognitive function. We evaluated the effects of cGP on spatial memory and histological changes in the hippocampus of the adult rats following infancy administration. Infant rats were treated with either cGP or saline between post-natal days 8 and 22 via oral administration to lactating dams. The spatial memory was evaluated between post-natal days 70 and 75 using Morris water maze tests. The changes of capillaries, astrocytes, synaptophysin and glutamate receptor-1 were examined in the CA1 stratum radiatum of the hippocampus. Compared to saline-treated group, cGP-treated group showed higher path efficiency of entry and lower average heading errors to the platform zone. cGP-treated group also showed longer, larger and more astrocytic processes, more capillaries and higher glutamate receptor-1 expression. The rats made less average heading error to the platform zone have more capillaries, larger and longer astrocytic branches. Thus cGP treatment/supplementation during infancy moderately improved adulthood spatial memory. This long-lasting effect of cGP on memory could be mediated via promoting astrocytic plasticity, vascularization and glutamate trafficking. Therefore, cGP may have a role in regulating IGF-1 function during brain development.

Effects of Polyphenols on P-Glycoprotein (ABCB1) Activity.

P-glycoprotein (Pgp, ABCB1) is a member of one of the largest families of active transporter proteins called ABC transporters. Thanks to its expression in tissues with barrier functions and its broad substrate spectrum, it is an important determinant of the absorption, metabolism and excretion of many drugs. Pgp and/or some other drug transporting ABC proteins (e.g., ABCG2, MRP1) are overexpressed in nearly all cancers and cancer stem cells by which cancer cells become resistant against many drugs. Thus, Pgp inhibition might be a strategy for fighting against drug-resistant cancer cells. Previous studies have shown that certain polyphenols interact with human Pgp. We tested the effect of 15 polyphenols of sour cherry origin on the basal and verapamil-stimulated ATPase activity of Pgp, calcein-AM and daunorubicin transport as well as on the conformation of Pgp using the conformation sensitive UIC2 mAb. We found that quercetin, quercetin-3-glucoside, narcissoside and ellagic acid inhibited the ATPase activity of Pgp and increased the accumulation of calcein and daunorubicin by Pgp-positive cells. Cyanidin-3O-sophoroside, catechin, naringenin, kuromanin and caffeic acid increased the ATPase activity of Pgp, while they had only a weaker effect on the intracellular accumulation of fluorescent Pgp substrates. Several tested polyphenols including epicatechin, trans-ferulic acid, oenin, malvin and chlorogenic acid were ineffective in all assays applied. Interestingly, catechin and epicatechin behave differently, although they are stereoisomers. We also investigated the effect of quercetin, naringenin and ellagic acid added in combination with verapamil on the transport activity of Pgp. In these experiments, we found that the transport inhibitory effect of the tested polyphenols and verapamil was additive or synergistic. Generally, our data demonstrate diverse interactions of the tested polyphenols with Pgp. Our results also call attention to the potential risks of drug-drug interactions (DDIs) associated with the consumption of dietary polyphenols concurrently with chemotherapy treatment involving Pgp substrate/inhibitor drugs.

Deep-LSTM ensemble framework to forecast Covid-19: an insight to the global pandemic.

The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is spreading all over the world. Medical health care systems are in urgent need to diagnose this pandemic with the support of new emerging technologies like artificial intelligence (AI), internet of things (IoT) and Big Data System. In this dichotomy study, we divide our research in two ways-firstly, the review of literature is carried out on databases of Elsevier, Google Scholar, Scopus, PubMed and Wiley Online using keywords Coronavirus, Covid-19, artificial intelligence on Covid-19, Coronavirus 2019 and collected the latest information about Covid-19. Possible applications are identified from the same to enhance the future research. We have found various databases, websites and dashboards working on real time extraction of Covid-19 data. This will be conducive for future research to easily locate the available information. Secondly, we designed a nested ensemble model using deep learning methods based on long short term memory (LSTM). Proposed Deep-LSTM ensemble model is evaluated on intensive care Covid-19 confirmed and death cases of India with different classification metrics such as accuracy, precision, recall, f-measure and mean absolute percentage error. Medical healthcare facilities are boosted with the intervention of AI as it can mimic human intelligence. Contactless treatment is possible only with the help of AI assisted automated health care systems. Furthermore, remote location self treatment is one of the key benefits provided by AI based systems.

Swing door technique for uncinectomy versus standard technique: a comparative study.

INTRODUCTION: Uncinectomy can be performed using various methods. The aim of the present study was to compare the results and complications of uncinectomy and middle meatus antrostomy using the standard and swing door techniques during functional endoscopic sinus surgery. METHODS: In a prospective controlled study, 60 patients (aged 18-50 years) suffering from chronic maxillary sinusitis underwent functional endoscopic sinus surgery from January 2007 to December 2008 at a tertiary care centre. The patients were randomly divided into two groups of 30: Group A underwent uncinectomy using the standard technique, while Group B underwent uncinectomy using the swing door technique. RESULTS: Group B showed more improvement in symptoms, with a mean visual analogue scale score of 80.58 ± 14.34 compared to 78.50 ± 16.63 in Group A. Both groups had no major complications. At the end of Week 2, minor complications were observed in 8 (26.7%) of the patients from Group A and 2 (6.7%) from Group B. By the sixth week, the minor complication rate was 1 (3.3%) and 0 (0%) in Group A and Group B, respectively. When compared statistically during the second week using chi-square test, the difference in the minor complication rate was found to be statistically significant (p < 0.05, χ2 = 4.81), with lower incidence of complications in Group B. CONCLUSION: The swing door technique for uncinectomy produces good postoperative results, with fewer complications, as compared to the standard technique.

Time series forecasting of Covid-19 using deep learning models: India-USA comparative case study.

Covid-19 is a highly contagious virus which almost freezes the world along with its economy. Its ability of human-to-human and surface-to-human transmission turns the world into catastrophic phase. In this study, our aim is to predict the future conditions of novel Coronavirus to recede its impact. We have proposed deep learning based comparative analysis of Covid-19 cases in India and USA. The datasets of confirmed and death cases of Covid-19 are taken into consideration. The recurrent neural network (RNN) based variants of long short term memory (LSTM) such as Stacked LSTM, Bi-directional LSTM and Convolutional LSTM are used to design the proposed methodology and forecast the Covid-19 cases for one month ahead. Convolution LSTM outperformed the other two models and predicts the Covid-19 cases with high accuracy and very less error for all four datasets of both countries. Upward/downward trend of forecasted Covid-19 cases are also visualized graphically, which would be helpful for researchers and policy makers to mitigate the mortality and morbidity rate by streaming the Covid-19 into right direction.

Cyclic-glycine-proline accelerates mammary involution by promoting apoptosis and inhibiting IGF-1 function.

In rodents, post-lactational involution of mammary glands is characterized by the loss of mammary epithelial cells via apoptosis, which is associated with a decline in the expression of insulin-like growth factor-1 (IGF-1). Overexpression of IGF-1 delays involution by inhibiting apoptosis of epithelial cells and preserving the remaining secretory alveoli. Cyclic-glycine-proline (cGP), a metabolite of IGF-1, normalizes IGF-1 function under pathological conditions by regulating the bioavailability of IGF-1. The present study investigated the effect of cGP on the physiological decline in IGF-1 function during post-lactational mammary involution. Rat dams were gavaged with either cGP (3 mg/kg) or saline once per day from post-natal d8-22. Before collecting tissue on post-natal d23, a pair of mammary glands were sealed on d20 (72 hr-engorgement, thus representative of late-involution) and d22 (24 hr-engorgement, thus representative of mid-involution), while the remaining glands were allowed to involute naturally (early-involution). During early-involution, cGP accelerated the loss of mammary cells through apoptosis, resulting in an earlier clearance of intact secretory alveoli compared with the control group. This coincided with an earlier up-regulation of the cell survival factors, Bcl-xl and IGF-1R, in the early-involution cGP glands compared with the control glands. During late-involution, cGP reduced the bioactivity of IGF-1, which was evident through decreased phosphorylation of IGF-1R in the regressed alveoli. Maternal administration of cGP did not alter milk production and composition during early-, peak-, or late-stage of lactation. These data show that cGP accelerates post-lactational involution by promoting apoptosis and the physiological decline in IGF-1 function.

Tight Junction Protein Abundance and Apoptosis During Involution of Rat Mammary Glands.

To examine tight junction protein abundance and apoptosis of epithelial cells at the onset of involution in rodent mammary glands, milk accumulation and mammary engorgement were induced by teat-sealing with an adhesive for 0, 6, 12, 18, 24, and 36 h (n = 6 per group) at peak lactation. In non-sealed control glands, histological analysis confirmed a lactating phenotype, indicating suckling by pups throughout the experiment. In contrast, alveoli of teat-sealed glands were distended within 6 h, with maximal luminal size observed by 12 h of non-suckling. By 18 h following teat-sealing, an involuting phenotype was observed, indicated by alveolar lumina engorged with milk vesicles and increased leukocytes. Relative to non-sealed glands, mammary apoptosis was increased in engorged glands 18 h following teat-sealing. The abundance of ZO-1 and occludin proteins was decreased in engorged glands by 12 and 18 h, respectively, following teat-sealing. In contrast, the claudin-1 22 kDa band was increased by 6 h and peaked at 12-18 h, whereas the 28 kDa band declined by 36 h, relative to controls. There were no temporal changes in ZO-1, occludin, and claudin-1 22 kDa proteins within control glands, although there were minor differences in claudin-1 28 kDa. These data indicate that intramammary milk accumulation due to cessation of milk removal is associated with mammary apoptosis. The apoptotic event is preceded by a rapid loss of abundance of ZO-1, occludin and an initial increase in claudin-1. The loss of cell-cell communication may initiate involution and apoptosis of mammary epithelial cells and is a localized intramammary event, occurring only in non-suckled glands. J. Cell. Physiol. 232: 2075-2082, 2017. © 2016 Wiley Periodicals, Inc.

Maternally Administered Cyclic Glycine-Proline Increases Insulin-Like Growth Factor-1 Bioavailability and Novelty Recognition in Developing Offspring.

Cyclic glycine-proline (cGP), a metabolite of IGF-1, is an endogenous neuropeptide that improves memory in adult rats. The presence and concentrations of endogenous cGP, and its association with IGF-1 and IGF binding protein-3 (IGFBP-3) in rat milk and plasma, were evaluated during postnatal development. Maternal-infantile transfer of cGP during lactation and its efficacy on the memory of developing offspring were also investigated. Dams were gavaged with either cGP (3 mg/kg) or saline daily from postnatal days 8-22. Concentrations of cGP were measured in dams' milk, and concentrations of cGP, IGF-1, and IGFBP-3 were measured in the plasma of dams, pups, and young adults. The recognition memory, locomotor function, and anxiety-like behavior of offspring were evaluated using behavioral tests. Endogenous cGP was detected in rat milk, and its concentration was higher during peak lactation compared with late lactation. Comparisons within control groups showed low endogenous IGF-1 and IGFBP-3 and high endogenous cGP concentrations in the plasma of male pups. The reduced IGFBP-3 and increased cGP may be a response to increase the bioavailability of IGF-1 during infancy. Exogenous cGP showed oral bioavailability and effective maternal-infantile transfer through milk. Maternally transferred cGP also led to improved recognition memory in the developing offspring, possibly through increased IGF-1 bioavailability, with no effect on locomotor activity and anxiety-like behavior. These results show that cGP is an essential endogenous peptide during early postnatal development as it improves the bioavailability of IGF-1 during infancy. Furthermore, maternal cGP supplementation offers an effective and natural route of administration for improving memory in the developing offspring.

Prenatal maternal and possible transgenerational epigenetic effects on milk production.

This study investigated whether the prenatal maternal environment in dairy cattle influences the postnatal milking performance of the resulting daughters and grand-daughters. Linear mixed models were used to analyse whole season milk production from ∼ 46,000 Jersey and ∼ 123,000 Holstein Friesian cows in their 1st and 2nd lactations. Variation in the prenatal environment was associated with a small but significant (P<0.05) proportion of the total phenotypic variation (0.010 to 0.015) in all traits in Holstein Friesian cows and in the first lactation milk volume (0.011) and milk protein (0.011), and the second lactation milk fat (0.015) in the Jersey breed. This indicates that the prenatal environment does influence the adult performance of the subsequent daughter. Associations between daughter performance and dam and grand-dam traits indicative of their prenatal environment were also estimated. A one litre increase in the dam's herd test milk volume was associated with a 7.5 litre increase in the daughters' whole season milk yield and a 1% increase in either the dams' herd test milk fat or protein percentage was associated with a reduction in daughter whole season milk volume (-49.6 and -45.0 litres for dam fat and protein, respectively). Similar results between the grand-dam herd test traits and the daughters' whole season milk production were observed with a 1% increase in either grand-dam milk fat or protein percentage associated with a reduction in daughter whole season milk yield (-34.7 and -9.7 litres for fat and protein, respectively). This study revealed that the prenatal environment of the dam and the grand-dam can influence milk production in the subsequent daughters, though the effects are small. The similarity of the results between the dam daughter and the grand-dam daughter analyses suggests that the majority of the prenatal maternal effects are mediated by epigenetic mechanisms.

The role of tight junctions in mammary gland function.

Tight junctions (TJ) are cellular structures that facilitate cell-cell communication and are important in maintaining the three-dimensional structure of epithelia. It is only during the last two decades that the molecular make-up of TJ is becoming unravelled, with two major transmembrane-spanning structural protein families, called occludin and claudins, being the true constituents of the TJ. These TJ proteins are linked via specific scaffolding proteins to the cell's cytoskeleton. In the mammary gland TJ between adjacent secretory epithelial cells are formed during lactogenesis and are instrumental in establishing and maintaining milk synthesis and secretion, whereas TJ integrity is compromised during mammary involution and also as result of mastitis and periods of mammary inflamation (including mastitis). They prevent the paracellular transport of ions and small molecules between the blood and milk compartments. Formation of intact TJ at the start of lactation is important for the establishment of the lactation. Conversely, loss of TJ integrity has been linked to reduced milk secretion and mammary function and increased paracellular transport of blood components into the milk and vice versa. In addition to acting as a paracellular barrier, the TJ is increasingly linked to playing an active role in intracellular signalling. This review focusses on the role of TJ in mammary function of the normal, non-malignant mammary gland, predominantly in ruminants, the major dairy producing species.

Characterization of primary cilia distribution and morphology during lactation, stasis, and involution in the bovine mammary gland.

Primary cilia are small, sensory organelles projecting from virtually all cells and are vital for cellular and tissue function. Their distribution in bovine mammary tissue has not previously been assessed, despite the potential for these organelles to provide specialized perceptive and regulatory functions to this acutely responsive and adaptive gland. The research objectives were to assess ciliary distribution and morphology during active lactation, milk stasis, and early involution using tissue samples obtained following the abrupt cessation of milk removal in nonpregnant, Friesian dairy cows at mid-lactation. Routinely processed tissue sections were obtained at intervals from 6 to 192 hr after the last milking (N = 3 animals per group) and assigned to active lactation (6-12 hr), milk stasis (18-36 hr), and early involution (72-192 hr). Primary cilia were observed in luminal secretory epithelial cells (SECs), myoepithelial cells, and stromal cells following fluorescent immunohistochemistry and confocal microscopy. In SECs, some primary cilia appeared deflected against the apical cell membrane. The proportion of those deflected was greater during milk stasis than active lactation. Data show that primary cilia were suitably placed in three important cell types to potentially coordinate various forms of signal transduction relying on both mechanosensation and chemosensation, according to the physical and physiological state of the gland. Their cell-type distribution and morphology provide new directions in the study of mammary regulation to enhance the understanding of how various mammary-specific cellular responses may be initiated by biochemical or local biophysical factors.