Role of apoptotic protease activating factor-1 in CD4+ depletion during HIV progression.

Objective: This study investigates the role of Apoptotic Protease Activating Factor-1 (APAF-1) in CD4+ cell depletion among human immunodeficiency virus (HIV) patients. Materials and Methods: This is a cross-sectional study in which 105 participants were enrolled, including 60 confirmed HIV-positive patients and 45 HIV-negative controls. HIV-positive patients were further divided based on CD4+ cell counts: Group 1 (<200), Group 2 (200-499), and Group 3 (≥500). An enzyme-linked immunoassay was used to measure APAF-1 levels, and CD4+ T-cell counts were enumerated using a Cyflow counter. Independent student's t-test, Kruskal-Wallis, and Spearman's correlation were utilized as needed. Results: Results showed significant reductions in lymphocytes, platelets, red blood cells, hemoglobin, albumin, and CD4+ cell values among HIV-infected individuals compared to controls. Conversely, APAF-1 and total protein levels were elevated in HIV-positive patients. Among HIV-positive groups, those with CD4+ cell counts <200 exhibited the highest median serum APAF-1 concentration. However, these differences were not statistically significant when compared with the other seropositive groups with CD4+ cell counts between 200 and 499 (P = 0.6726) and CD4+ cell counts of 500 or greater (P = 0.4325). The control group had the lowest median SAPAF-1 concentration, significantly different from HIV-positive groups. Positive correlations were observed between CD4+ counts and lymphocytes, hemoglobin, and hypoalbuminemia, while negative correlations were found between these parameters and APAF-1 levels. Conclusion: APAF-1 is a host factor that potentially contributes to CD4+ cell depletion. Similarly, APAF-1, serum total protein, and albumin levels were found to be predictive of disease progression and could serve as valuable diagnostic biomarkers in the monitoring of HIV/AIDS.

Serological review of Bartonella henselae and Bartonella quintana infection among Malaysian patients with unknown causes of febrile illnesses.

Limited information is available on human exposure to Bartonella infection, i.e., Bartonella henselae (causative agent of cat scratch disease) and Bartonella quintana (causative agent of trench fever) in West Malaysia. This study reports a review of serological findings obtained from patients attending to a teaching hospital in Klang Valley, Malaysia. An indirect immunofluorescence assay (IFA) was used to determine IgG and IgM antibody titers against B. henselae and B. quintana. In a pilot study conducted between 2013-2015, IgG antibodies against Bartonella spp. (either B. quintana and B. henselae) were detected in 14 (36.8%) of 38 patients who were clinically suspected of rickettsial infections, while IgM antibody was detected in 4 (10.5%) patients. This has prompted us to investigate the serologic responses of patients who were clinically suspected of other febrile causes besides rickettsial infection. Of the 59 serum samples analysed in a follow-up investigation, Bartonella IgG antibodies were detected from 7 (11.9%) patients, of which 5 (27.8%) and 2 (18.2%) patients were clinically suspected of rickettsial infection (n=18) and dengue (n=11), respectively. None of the sera obtained from the leptospirosis (n=10), legionellosis (n=10) and mycoplasma infection (n=10) groups were seropositive to Bartonella spp. The review of Bartonella serological findings in this study highlights that Bartonella infection is not uncommon and should be considered as one of the causes for febrile illness in Malaysia.

Serological review of Bartonella henselae and Bartonella quintana infection among Malaysian patients with unknown causes of febrile illnesses

@#Limited information is available on human exposure to Bartonella infection, i.e., Bartonella henselae (causative agent of cat scratch disease) and Bartonella quintana (causative agent of trench fever) in West Malaysia. This study reports a review of serological findings obtained from patients attending to a teaching hospital in Klang Valley, Malaysia. An indirect immunofluorescence assay (IFA) was used to determine IgG and IgM antibody titers against B. henselae and B. quintana. In a pilot study conducted between 2013-2015, IgG antibodies against Bartonella spp. (either B. quintana and B. henselae) were detected in 14 (36.8%) of 38 patients who were clinically suspected of rickettsial infections, while IgM antibody was detected in 4 (10.5%) patients. This has prompted us to investigate the serologic responses of patients who were clinically suspected of other febrile causes besides rickettsial infection. Of the 59 serum samples analysed in a follow-up investigation, Bartonella IgG antibodies were detected from 7 (11.9%) patients, of which 5 (27.8%) and 2 (18.2%) patients were clinically suspected of rickettsial infection (n=18) and dengue (n=11), respectively. None of the sera obtained from the leptospirosis (n=10), legionellosis (n=10) and mycoplasma infection (n=10) groups were seropositive to Bartonella spp. The review of Bartonella serological findings in this study highlights that Bartonella infection is not uncommon and should be considered as one of the causes for febrile illness in Malaysia.

Early survey with bibliometric analysis on machine learning approaches in controlling coronavirus

Background and ObjectiveThe COVID-19 pandemic has caused severe mortality across the globe with the USA as the current epicenter, although the initial outbreak was in Wuhan, China. Many studies successfully applied machine learning to fight the COVID-19 pandemic from a different perspective. To the best of the authors knowledge, no comprehensive survey with bibliometric analysis has been conducted on the adoption of machine learning for fighting COVID-19. Therefore, the main goal of this study is to bridge this gap by carrying out an in-depth survey with bibliometric analysis on the adoption of machine-learning-based technologies to fight the COVID-19 pandemic from a different perspective, including an extensive systematic literature review and a bibliometric analysis. MethodsA literature survey methodology is applied to retrieve data from academic databases, and a bibliometric technique is subsequently employed to analyze the accessed records. Moreover, the concise summary, sources of COVID-19 datasets, taxonomy, synthesis, and analysis are presented. The convolutional neural network (CNN) is found mainly utilized in developing COVID-19 diagnosis and prognosis tools, mostly from chest X-ray and chest computed tomography (CT) scan images. Similarly, a bibliometric analysis of machine-learning-based COVID-19-related publications in Scopus and Web of Science citation indexes is performed. Finally, a new perspective is proposed to solve the challenges identified as directions for future research. We believe that the survey with bibliometric analysis can help researchers easily detect areas that require further development and identify potential collaborators. ResultsThe findings in this study reveal that machine-learning-based COVID-19 diagnostic tools received the most considerable attention from researchers. Specifically, the analyses of the results show that energy and resources are more dispensed toward COVID-19 automated diagnostic tools, while COVID-19 drugs and vaccine development remain grossly underexploited. Moreover, the machine-learning-based algorithm predominantly utilized by researchers in developing the diagnostic tool is CNN mainly from X-rays and CT scan images. ConclusionsThe challenges hindering practical work on the application of machine-learning-based technologies to fight COVID-19 and a new perspective to solve the identified problems are presented in this study. We believe that the presented survey with bibliometric analysis can help researchers determine areas that need further development and identify potential collaborators at author, country, and institutional levels to advance research in the focused area of machine learning application for disease control.

Implications of SARS-CoV-2 genetic diversity and mutations on pathogenicity of the COVID-19 and biomedical interventions.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused an unprecedented global health emergency. The COVID-19 pandemic has claimed over 350,000 human lives within five months of its emergence, especially in the USA and the European continent. This study analysed the implications of the genetic diversity and mutations in SARS-CoV-2 on its virulence diversity and investigated how these factors could affect the successful development and application of antiviral chemotherapy and serodiagnostic test kits, and vaccination. METHODS: All the suitable and eligible full text articles published between 31st December 2019 and 31st May 2020 were filtered and extracted from "PubMed", "Scopus", "Web of Science", and "Hinari" and were critically reviewed. We used the Medical Subject Headings (MeSH) terms "COVID-19, "Mutation", "Genetic diversity", "SARS-CoV-2", "Virulence", "Pathogenicity", "Evolution" and "SARS-CoV-2 transmission" for this search. RESULTS: Our search showed that SARS-CoV-2 has persistently undergone significant mutations in various parts of its non-structural proteins (NSPs) especially NSP2 and NSP3, S protein, and RNA-dependent RNA polymerase (RdRp). In particular, the S protein was found to be the key determinant of evolution, transmission, and virulence of SARS-CoV-2, and could be a potential target for vaccine development. Additionally, RdRp could be a major target in the development of antivirals for the treatment of COVID-19. CONCLUSION: Given the critical importance of mutations in the pathogenicity of SARS-CoV-2 and in the development of sero-diagnostics, antivirals, and vaccines, this study recommends continuous molecular surveillance of SARS-CoV-2. This approach would potentially prompt identification of new mutants and their impact on ongoing biomedical interventions and COVID-19 control measures.

(3S)-3-(2,3-difluorophenyl)-3-methoxypyrrolidine (IRL752) -a Novel Cortical-Preferring Catecholamine Transmission- and Cognition-Promoting Agent.

Here we describe for the first time the distinctive pharmacological profile for (3S)-3-(2,3-difluorophenyl)-3-methoxypyrrolidine (IRL752), a new phenyl-pyrrolidine derivative with regioselective central nervous system transmission-enhancing properties. IRL752 (3.7-150 µmol/kg, s.c.) was characterized through extensive in vivo studies using behavioral, tissue neurochemical, and gene expression as well as microdialysis methods. Behaviorally, the compound normalized tetrabenazine-induced hypoactivity, whereas it was unable to stimulate basal locomotion in normal animals or either accentuate or reverse hyperactivity induced by amphetamine or MK-801. IRL752 induced but minor changes in monoaminergic tissue neurochemistry across noradrenaline (NA)- and dopamine (DA)-dominated brain regions. The expression of neuronal activity-, plasticity-, and cognition-related immediate early genes (IEGs), however, increased by 1.5-fold to 2-fold. Furthermore, IRL752 dose-dependently enhanced cortical catecholamine dialysate output to 600%-750% above baseline, whereas striatal DA remained unaltered, and NA rose to ∼250%; cortical and hippocampal dialysate acetylcholine (ACh) increased to ∼250% and 190% above corresponding baseline, respectively. In line with this cortically preferential transmission-promoting action, the drug was also procognitive in the novel object recognition and reversal learning tests. In vitro neurotarget affinity and functional data coupled to drug exposure support the hypothesis that 5-hydroxytryptamine 7 receptor and α2(C)-adrenoceptor antagonism are key contributors to the in vivo efficacy and original profile of IRL752. The cortical-preferring facilitatory impact on catecholamine (and ACh) neurotransmission, along with effects on IEG expression and cognition-enhancing features, are in line with the potential clinical usefulness of IRL752 in conditions wherein these aspects may be dysregulated, such as in axial motor and cognitive deficits in Parkinson disease. SIGNIFICANCE STATEMENT: This report describes the distinctive preclinical profile of (3S)-3-(2,3-difluorophenyl)-3-methoxypyrrolidine (IRL752). Its in vivo neurochemical, behavioral, microdialysis, and gene expression properties are consistent with a cortically regioselective facilitatory impact on catecholaminergic and cholinergic neurotransmission accompanied by cognitive impairment-reversing features. The pharmacological characteristics of IRL752 are in line with the clinical usefulness of IRL752 in conditions wherein these aspects may be dysregulated, such as in axial motor and cognitive deficits in Parkinson disease.

Spectral analysis of Miracle Moringa tree leaves using X-ray photoelectron, laser induced breakdown and inductively coupled plasma -optical emission spectroscopic techniques.

The antioxidant Moringa oleifera (a medicinal plant) leaves (MOLs) containing diverse nutrients are highly beneficial for the human health. The MOLs upon consumption can lower the blood sugar, cure the heart diseases, and reduce the inflammation. In this perception, the "primary nutrients contents" in the dry MOLs (pellet samples) were evaluated for the first time using the XPS, LIBS and ICP-OES techniques. The XPS analysis of the MOLs showed the presence of vital elements like calcium (Ca), magnesium (Mg), manganese (Mn), copper (Cu), phosphorous (P), sulfur (S) and zinc (Zn). The LIBS analyses of the MOLs revealed the atomic and ionic spectral lines corresponding to the essential nutrients such as the Ca, Na, K, Fe, Mg, Mn, Cu, P, S and Zn. The calibration free LIBS algorithm (CF-LIBSA) was developed to quantify the content of each element in the dry MOLs. In addition, the LIBS results were validated by the analysis using ICP-OES standard analytical technique. The elemental contents in the MOLs obtained from the CF-LIBS analyses were counter verified by the ICP-OES results. Present results are highly valuable for the development of a traditional herbal medicine using the miracle MOLs.

A Machine Learning Solution Framework for Combatting COVID-19 in Smart Cities from Multiple Dimensions

The spread of COVID-19 across the world continues as efforts are being made from multi-dimension to curtail its spread and provide treatment. The COVID-19 triggered partial and full lockdown across the globe in an effort to prevent its spread. COVID-19 causes serious fatalities with United States of America recording over 3,000 deaths within 24 hours, the highest in the world for a single day and as of October 2020 has recorded a total of 270,642 death toll. In this paper, we present a novel framework which intelligently combines machine learning models and internet of things (IoT) technology specific in combatting COVID-19 in smart cities. The purpose of the study is to promote the interoperability of machine learning algorithms with IoT technology in interacting with a population and its environment with the aim of curtailing COVID-19. Furthermore, the study also investigates and discusses some solution frameworks, which can generate, capture, store and analyze data using machine learning algorithms. These algorithms are able to detect, prevent, and trace the spread of COVID-19, and provide better understanding of the virus in smart cities. Similarly, the study outlined case studies on the application of machine learning to help in the fight against COVID-19 in hospitals across the world. The framework proposed in the study is a comprehensive presentation on the major components needed for an integration of machine learning approach with other AI-based solutions. Finally, the machine learning framework presented in this study has the potential to help national healthcare systems in curtailing the COVID-19 pandemic in smart cities. In addition, the proposed framework is poised as a point for generating research interests which will yield outcomes capable of been integrated to form an improved framework.

Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks.

BACKGROUND AND OBJECTIVE: The COVID-19 pandemic has caused severe mortality across the globe, with the USA as the current epicenter of the COVID-19 epidemic even though the initial outbreak was in Wuhan, China. Many studies successfully applied machine learning to fight COVID-19 pandemic from a different perspective. To the best of the authors' knowledge, no comprehensive survey with bibliometric analysis has been conducted yet on the adoption of machine learning to fight COVID-19. Therefore, the main goal of this study is to bridge this gap by carrying out an in-depth survey with bibliometric analysis on the adoption of machine learning-based technologies to fight COVID-19 pandemic from a different perspective, including an extensive systematic literature review and bibliometric analysis. METHODS: We applied a literature survey methodology to retrieved data from academic databases and subsequently employed a bibliometric technique to analyze the accessed records. Besides, the concise summary, sources of COVID-19 datasets, taxonomy, synthesis and analysis are presented in this study. It was found that the Convolutional Neural Network (CNN) is mainly utilized in developing COVID-19 diagnosis and prognosis tools, mostly from chest X-ray and chest CT scan images. Similarly, in this study, we performed a bibliometric analysis of machine learning-based COVID-19 related publications in the Scopus and Web of Science citation indexes. Finally, we propose a new perspective for solving the challenges identified as direction for future research. We believe the survey with bibliometric analysis can help researchers easily detect areas that require further development and identify potential collaborators. RESULTS: The findings of the analysis presented in this article reveal that machine learning-based COVID-19 diagnose tools received the most considerable attention from researchers. Specifically, the analyses of results show that energy and resources are more dispenses towards COVID-19 automated diagnose tools while COVID-19 drugs and vaccine development remains grossly underexploited. Besides, the machine learning-based algorithm that is predominantly utilized by researchers in developing the diagnostic tool is CNN mainly from X-rays and CT scan images. CONCLUSIONS: The challenges hindering practical work on the application of machine learning-based technologies to fight COVID-19 and new perspective to solve the identified problems are presented in this article. Furthermore, we believed that the presented survey with bibliometric analysis could make it easier for researchers to identify areas that need further development and possibly identify potential collaborators at author, country and institutional level, with the overall aim of furthering research in the focused area of machine learning application to disease control.

Prevalence and Management of Septic Shock among Children Admitted at the Kenyatta National Hospital, Longitudinal Survey.

BACKGROUND: Paediatric septic shock is a subset of sepsis associated with high mortality. Implementing the existing international Surviving Sepsis Campaign Guidelines 2012 (SSCG) have contributed to reduction of mortality in many places but these have not been adopted in our setting. The current study aimed at documenting the practice at a national referral hospital. METHODS: A hospital based longitudinal survey carried out among 325 children from September to October 2016. Children aged 0 days (≥37 weeks gestation) to12 years were included. The aim was to determine the prevalence, audit the management and determine the outcome at 72 hours of septic shock among children admitted at the Kenyatta National Hospital (KNH). A standard questionnaire was used for data collection and Surviving Sepsis Guideline 2012 was used as a reference for auditing the management of septic shock. Data was stored in MS-EXCEL and analysed in STATA 12. RESULTS: The prevalence of septic shock was 50 (15.4%), with a median age of 4 months. Septic shock was recognized by the attending clinician in 28 (56%). The level of care to children with septic shock was not to the level recommended by the SSCG 2012. Odds of being diagnosed with septic shock reduced with age (odds ratio 4.38 (1.7-11.0), p = 0.002) and no child aged above 60 months age was diagnosed with septic shock. The mortality was 35 (70%) at 72 hours of admission, with a median of 14 hours. Infants had the highest case fatality of 82.6%. It was found that lack of mechanical ventilation, and presence of hypotension at admission were associated with greater mortality (p values of 0.03 and 0.01 respectively). CONCLUSION: The prevalence rate of septic shock is 15.4% among children admitted at the KNH and is associated with high mortality. The advanced degree of shock contributed to mortality. The level of care at KNH was not to the level of SSCG 2012, and hence the need to include septic shock management guidelines/protocols in our local Kenyan paediatric guideline.

H-D Analysis Employing Energy Transfer from Metastable Excited-State He in Double-Pulse LIBS with Low-Pressure He Gas.

A laser-induced-breakdown-spectroscopy (LIBS) experiment with a unique double-pulse setup and operated in low-pressure (3 kPa) He ambient gas is performed to study the detection of light elements, such as hydrogen (H) and deuterium (D), as well as elements of high excitation energies, such as fluorine (F) and chlorine (Cl), which are usually difficult to detect using ordinary LIBS techniques. A nanosecond Nd:YAG laser operated in its fundamental wavelength with energy of 54 mJ is focused onto the Al target to generate the He plasma. Another picosecond Nd:YAG laser operated in its fundamental wavelength with energy of 2 mJ is focused onto the sample surface and activated 2 µs before the operation of the nanosecond laser. The application to polyvinyl chloride (PVC) and polytetrafluoroethylene (PTFE) samples produces sharp and high-intensity Cl- and F-emission lines. Meanwhile, the sharp and well-resolved H-D-emission lines with merely 0.18 nm wavelength separation are also clearly detected from a zircaloy sample. Further measurement of a set of zircaloy samples containing different concentrations of D yields a linear calibration curve with a zero intercept. The detection limit of D is found to be about 10 ppm.

Gonococcal conjunctivitis: A case report.

We report a case of acute gonococcal conjunctivitis in a 36-year-old woman who presented with eye redness and a history of discharge for one month. Prior to presenting to us, she was treated for bacterial conjunctivitis with three courses of local antibiotics by three different clinics after brief assessments and without improvement. The final diagnosis of gonococcal conjunctivitis was made after a complete history was elicited and supported by the presence of Neisseria Gonorrhoeae in the eye swab culture test. She and her sexual partner were treated successfully with intramuscular Ceftriaxone and oral Azithromycin. This case highlights the importance of complete history taking, including sexual history, which translates into early recognition and treatment, thus preventing complications.

Pontamine fast scarlet 4B bifluorescence and measurements of cellulose microfibril angles.

Pontamine fast scarlet 4B is a red paper and textiles dye that has recently been introduced as a fluorescent probe for plant cell walls. Pontamine exhibits bifluorescence, or fluorescence dependent on the polarization of the excitation light: Because cellulose is aligned within the cell wall, pontamine-labelled cell walls exhibit variable fluorescence as the excitation polarization is modulated. Thus, bifluorescence measurements require polarized excitation that can be directly or indirectly modulated. In our confocal microscopy observations of various cellulose samples labelled with pontamine, we modulated excitation polarization either through sample rotation or by the confocal's scanfield rotation function. This variably rotated laser polarizations on Leica confocal microscopes, but not those from other makers. Beginning with samples with directly observable microfibril orientations, such as purified bacterial cellulose, the velamen of orchid roots and the inner S2 layer of radiata pine compression wood, we demonstrate that modelling the variations in pontamine fluorescence with a sine curve can be used to measure the known microfibril angles. We then measured average local microfibril angles in radiata pine samples, and showed similar microfibril angles in compression and normal (opposite) wood. Significantly, bifluorescence measurements might also be used to understand the degree of local cellulose alignment within the cell wall, as opposed to variations in the overall cellulose angle.

Interet de l'analyse du ganglion sentinelle dans le traitement du cancer du colon

L'objectif de ce travail est d'evaluer la performance de l'identification des micrometastases par l'analyse du ganglion sentinelle dans le traitement du cancer du colon classe initialement pTN0 et ceci dans le but de selectionner un sous groupe de patients qui beneficieront d'un traitement adjuvant. Materiels et methodes : Il s'agit d'une etude observationnelle effectuee au niveau de la clinique chirurgicale B du CHU Alger entre 2009 et 2013 .Nous avons pris en charge 61 patients; 40 hommes et 21 femmes ; l'age moyen etait de 58 ans. La laparotomie mediane etait la voie d'abord exclusive; nous avons realise 37;70% de sigmoidectomies; 29;51% hemicolectomies droites; 16;39 % resections segmentaires hautes ;1 transvesrsectomie vraie ; 6;56% d' hemicolectomies gauches ; 4;92% de colectomies totales et 2 coloproctectomies.Tous nos patients ont beneficie de l'epreuve au bleu methylene pour rechercher le ganglion sentinelle . Resultats : Le taux de detection du ganglion sentinelle etait de 98;36%; (164 ganglions sentinelles); dont 97;72% in vivo; un seul patient a beneficie de la technique ex vivo. Le taux de faux negatifs etait de 18;03%; la sensibilite de 47;62% et la valeur predictive negative est de 75%.L'etude immuno histochimique des ganglions sentinelles nous a permis d'identifier 7 micrometastases representant un taux de 17;5% et de reclasser (upstaging) 7 patients en pTN0i+ leur permettant de beneficier d'un traitement adjuvant. Au total 45;90 % de patients (34;42% avant l'etude immunohistochimique) avaient une atteinte ganglionnaire dont 75% apres une coloration HES et 25 % apres etude IHC. La survie sans recidive a 36 mois etait de 100% pour le sous groupe de patients classe pTN 0i+ alors qu'elle etait de 79% pour les patients classes pTN 0i- avec une difference non significative (p=0;5) et de 45;82% pour les patients classes pTN+; avec une difference significative (p=0;01) ;et le taux de mortalite etait nul pour les 2 groupes de patients classes pTN 0i+ et pTN 0i- alors qu'il etait de 14;28% pour les patients classes pTN+.Discussion : Le taux de detection du ganglion sentinelle varie entre 70 et 100% selon les differentes series publiees (98;36 dans notre serie). L' immuno histochimie est une technique qui permet de detecter des micrometastases dont la taille ne depasse pas 2 mm non visibles par les methodes anatomopathologiques standards et donc d'identifier un sous groupe de patients qui pourront beneficier d'un traitement adjuvant. Les differents travaux publies ont demontre la superiorite des methodes de biologie moleculaire (PCR / -RT-PCR); mais necessitent un materiel plus specifique et couteux. Le taux de faux negatif est important; mais n'influence pas la prise en charge chirurgicale des cancers coliques. La technique du ganglion sentinelle permet de reperer des trajets aberrants; qui sont reseques dans le meme temps operatoire; aucune etude n'a demontre l'impact pronostique de ces trajets. Le taux de survie sans recidive; etait meilleur chez les patients avec micrometastases ayant beneficie d'un traitement adjuvant; ceci suppose que la detection des micrometastases aurait un impact sur le traitement et le pronostic des cancers coliques; mais vu l'echantillon de cette etude; on ne peut pas se prononcer d'une maniere significative et ceci malgre les bons resultats des dernieres etudes (109) (110) Conclusion : La technique du ganglion sentinelle dans la prise en charge des cancers coliques est faisable; facile et reproductible ; elle permet d'identifier un sous groupe de patients presentant des micrometastases detectees par methodes immunohistochimiques Son impact sur le pronostic n'est pas statistiquement bien etabli malgre les resultats encourageants retrouves dans cette etude; et doivent etre confirmes par d'autres etudes multicentriques a grande echelle

Vitamin B12 deficiency presenting as pancytopenia in pregnancy: a case report.

Vitamin B12 deficiency is a well-known cause of megaloblastic anaemia and pancytopenia. However, the incidence in pregnancy is rarely reported. We present a case of a 32-year old multigravid woman who was diagnosed with megaloblastic anaemia since 22 weeks gestation and progressed to develop severe pancytopenia at 30 weeks gestation. She was also diagnosed with vitamin B12 deficiency related to dietary and sociocultural habits. Folate and iron levels were normal throughout pregnancy. Treatment with parenteral cyano-cobalamin resulted in sustained improvement of haematological parameters. The pregnancy was carried to term and the baby was born weighing 2,050gm but otherwise well at birth and had normal developmental milestones thereafter. This case illustrates the clinical presentation of maternal vitamin B12 deficiency and demonstrates the importance of detecting and treating maternal vitamin B12 deficiency during pregnancy in at-risk patients. Failure to diagnose and institute treatment carries significant risks to both mother and child. Oral vitamin B12 supplementation should be considered for patients who are strict vegetarians or consume very little animal products.

Ductus venosus velocimetry in monitoring pregnancy in women with pregestational diabetes mellitus.

OBJECTIVE: The purpose of this research was to assess the ability of ductus venosus (DV) Doppler velocimetry to predict adverse perinatal outcome in pregnancies complicated by pre-existing diabetes mellitus. METHODS: This was a prospective study conducted at a tertiary referral obstetric facility in Brisbane, Australia. The study group included women with pregestational diabetes mellitus who delivered in the hospital between 1 January 1995 and 31 December 2006. The DV Doppler index was defined as abnormal if the DV peak velocity index for veins (PVIV) was equal to or greater than the 95(th) percentile for gestation. Adverse perinatal outcome included one or more of the following criteria: small-for-gestational-age infant; Cesarean section for non-reassuring fetal status; fetal acidemia at delivery; a 1-min Apgar score of

Influence of polyhydramnios on perinatal outcome in pregestational diabetic pregnancies.

OBJECTIVE: This study was carried out to evaluate the perinatal outcomes of pregnancy with pregestational diabetes mellitus complicated by polyhydramnios. METHODS: This was a retrospective study of singleton pregnancies, with an antepartum diagnosis of polyhydramnios, seen at the maternal fetal medicine department of Mater Mothers' Hospital, a tertiary-level facility. All pregnancies in women with pregestational diabetes with a singleton pregnancy beyond 24 weeks of gestation, from 1996 to 2006, were reviewed (n = 314), and pregnancies complicated by polyhydramnios were identified (n = 59). Pregnancy outcomes of women whose pregnancy was complicated with polyhydramnios were compared to those without this complication. RESULTS: The incidence of polyhydramnios in the study population was 18.8%. Women with polyhydramnios had increased hemoglobin A1c (HbA1c) levels throughout the pregnancy, and the difference was significant during the prepregnancy period and in the third trimester (P = 0.003 and P = 0.025, respectively). Significantly more mothers in the polyhydramnios group delivered preterm (54.2% vs. 33.3%, P = 0.004), the majority of which were iatrogenic preterm deliveries (44.1%). More pregnancies with polyhydramnios were delivered by Cesarean section (83.0% vs. 62%; P = 0.006), with the majority being performed electively in both groups (79.6% and 70.3%, respectively). Regardless, there were no significant differences in perinatal mortality rates, congenital abnormality rates, the incidences of low Apgar score, acidemia, hypoglycemia requiring intravenous therapy, phototherapy and ventilatory needs between the babies of the two groups. CONCLUSION: Pregestational diabetic pregnancy with polyhydramnios is associated with poor diabetic control. Despite this, there is no significant increase in adverse perinatal outcome in these pregnancies, apart from a higher iatrogenic preterm birth rate.

Pregnancy in type 2 diabetes mellitus--problems & promises.

The parallel epidemics of obesity and Type 2 diabetes (T2DM) are progressing rapidly in Australia. The high prevalence of obesity and sedentary lifestyle in the population, compounded by later child bearing, has led to an increase in the prevalence of T2DM pre-dating pregnancy. In some centers, pregnant women with T2DM now outnumber those with type 1 diabetes (T1DM). Although there is controversy as to whether T2DM is associated with worse outcomes than T1DM in pregnancy, modern reports clearly acknowledge the seriousness of this condition. There is a clear association between obesity and adverse pregnancy outcomes (cesarean section, gestational diabetes, hypertensive disorders, birth defects and prematurity). Aside from obesity and the metabolic syndrome, additional factors may contribute to these adverse outcomes: A lack of preconception planning, a failure to achieve tight glycaemic control early in pregnancy and socio-economic disadvantage. It's likely that obesity and diabetes have compounding effects on pregnancy outcomes. In this review, we evaluate both the underlying pathogenesis of T2DM and obesity in the pregnancy context and the adverse clinical maternal and perinatal outcomes described in pregnancies complicated by maternal T2DM and obesity. We highlight the need for a comprehensive strategy to improve clinical outcomes in these pregnancies.

Universal versus selective screening for detection of gestational diabetes mellitus in a malaysian population.

OBJECTIVES: To compare the efficacy of two screenings methods for gestational diabetes mellitus, namely the universal screening using 50g Glucose Challenge Test to that of selective screening based on risk factors. METHODOLOGY: A cross-sectional study involving 366 women between 24 weeks to 28 weeks gestation who attended a community health clinic for their antenatal care between January to May 2003. All women had their risk factors for gestational diabetes identified at the beginning of the study, after which they underwent a 50g Glucose Challenge Test and subsequently the 75g Oral Glucose Tolerance Test. RESULTS: The prevalence of gestational diabetes mellitus in this population was 18.3%. The universal screening had a sensitivity of 83.5% and specificity of 82.6% compared to that of selective screening, 76.1% and 60.9% respectively. Of all patients diagnosed to have gestational diabetes mellitus, 23.8% were without risk factors. CONCLUSION: Universal screening strategy using 50g glucose challenge test is a better predictor of gestational diabetes mellitus compared to risk-based selective screening.