Latent TB treatment regimens in 2023: Wetmore TB clinic in New Orleans.

The USPSTF has updated Latent TB Infection (LTBI) screening and treatment recommendations in 2023; describing treatment courses, side effects and benefits associated with each regimen. Overall, rifampin-containing shortened regimens are the preferred modality for LTBI treatment. A recent study in 2023 evaluated adherence and tolerance of the isoniazid(INH) + rifapentine(RPT), or "3HP" regimen and identified patient groups that may be at higher risk for non-completion of this regimen. It emphasized the need for targeted education at the beginning of treatment, to avoid early discontinuation. Our experience in New Orleans demonstrated that the 3HP is well-tolerated, with higher completion rates than other LTBI regimens. Utilizing a retrospective chart review model, we reviewed 756 patients who were treated for LTBI over a two-year period from 1/2021--12/2022. The three possible treatment regimens included isoniazid (INH) alone, rifampin (RIF) alone, or INH + RPT (3HP). Of these regimens, the highest completion rate was in the 3HP group, despite literature suggesting this regimen is difficult to tolerate. Our experience suggests that this may still be an efficacious regimen that is well-tolerated if there is good access to clinicians to discuss mitigating side effects. More data is needed to determine factors that led to the success or failure for each regimen. Our clinic does have increased availability of nursing and medical staff to discuss side effects and answer questions, which may have contributed to our relatively higher success rate. In addition, we applied the review recommendations to our patient population, and would recommend the consideration of diabetes, heavy alcohol use, and tobacco use as risk factors for patients that would benefit from LTBI screening and treatment.

Evaluating Outcomes of Nonaccidental Trauma in Military Children.

BACKGROUND: Nonaccidental trauma (NAT), or child abuse, is a leading cause of childhood injury and death in the US. Studies demonstrate that military-affiliated individuals are at greater risk of mental health complication and family violence, including child maltreatment. There is limited information about the outcomes of military children who experience NAT. This study compares the outcomes between military-dependent and civilian children diagnosed with NAT. STUDY DESIGN: A single-institution, retrospective review of children admitted with confirmed NAT at a Level I trauma center was performed. Data were collected from the institutional trauma registry and the Child Abuse Team's database. Military affiliation was identified using insurance status and parental or caregiver self-reported active-duty status. Demographic and clinical data including hospital length of stay (LOS), morbidity, specialty consult, and mortality were compared. RESULTS: Among 535 patients, 11.8% (n = 63) were military-affiliated. The median age of military-associated patients, 3 months (interquartile range [IQR] 1 to 7), was significantly younger than civilian patients, 7 months (IQR 3 to 18, p < 0.001). Military-affilif:ated patients had a longer LOS of 4 days (IQR 2 to 11) vs 2 days (IQR 1 to 7, p = 0.041), increased morbidity or complication (3 vs 2 counts, p = 0.002), and a higher mortality rate (10% vs 4%, p = 0.048). No significant difference was observed in the number of consults or injuries, trauma activation, or need for surgery. CONCLUSIONS: Military-affiliated children diagnosed with NAT experience more adverse outcomes than civilian patients. Increased LOS, morbidity or complication, and mortality suggest military-affiliated patients experience more life-threatening NAT at a younger age. Larger studies are required to further examine this population and better support at-risk families.

Serum Raman spectroscopy: Evaluation of tumour load variations in experimental carcinogenesis.

Several serum Raman spectroscopy (RS) studies have demonstrated its potential as an oral cancer screening tool. This study investigates influence of low tumour load (LTL) and high tumour load (HTL) on serum RS using hamster buccal pouch model of experimental oral carcinogenesis. Sera of untreated control, LTL, and HTL groups at week intervals during malignant transformation were employed. Serum Raman spectra were subjected to multivariate analyses-principal component analysis, principal component-based linear discriminant analysis (for stratification of study groups), and multivariate curve resolution-alternating least squares (MCR-ALS) (to comprehend biomolecular differences). Multivariate analysis revealed misclassifications between LTL and HTL at all week intervals. MCR-ALS components showed statistically significant abundances between control versus LTL and control versus HTL, but could not discern LTL and HTL. MCR-ALS components exhibited spectral mixtures of proteins, lipids, heme and nucleic acids. Thus, these findings support use of serum RS as a screening tool as varying tumour load is not a confounding factor influencing the technique.

Application of a Machine Learning Algorithm in Prediction of Abusive Head Trauma in Children.

PURPOSE: We explored the application of a machine learning algorithm for the timely detection of potential abusive head trauma (AHT) using the first free-text note of an encounter and demographic information. METHODS: First free-text physician notes and demographic information were collected for children under 5 years of age at a Level 1 Trauma Center. The control group, which included patients with head/neck injury, was compared to those with AHT diagnosed by the Child Protective Team. Differential scores accounted for words overrepresented in AHT patient vs. control notes. Sentiment scores were reflective of note positivity/negativity and subjectivity scores accounted for note subjectivity/objectivity. The composite scores reflected the patient's differential score modified by the subjectivity score. Composite, sentiment, and subjectivity scores combined with demographic information trained a Random Forest (RF) machine learning algorithm to predict AHT. RESULTS: Final composite scores with demographic information were highly associated with AHT in a test dataset. The control group included 587 patients and the test group included 193 patients. Combining composite scores with demographic information into the RF model improved AHT classification area under the curve (AUC) from 0.68 to 0.78, with an overall accuracy of 84%. Feature importance analysis of our RF model revealed that composite score, sentiment, age, and subjectivity were the most impactful predictors of AHT. The sentiment was not significantly different between control and AHT notes (p = 0.87), while subjectivity trended higher for AHT notes (p = 0.081). CONCLUSION: We conclude that a machine learning algorithm can recognize patterns within free-text notes and demographic information that aid in AHT detection in children. LEVEL OF EVIDENCE: III.

Use of Multiple Fluid Biomarkers for Predicting the Co-occurrence of Diabetes and Hypertension Using Machine Learning Approaches.

The co-existence of diabetes and hypertension can complicate and affect the management of these diseases. The early detection of these comorbidities can help in developing personalized preventive treatments and thereby, reduce the healthcare burden. The inclusion of readily available fluid biomarkers from different body fluids can be used as diagnostic tools and can facilitate in the designing of treatment strategies. In this work, an attempt has been made using multiple fluid biomarkers to differentiate diabetic from diabetic and hypertensive comorbid (DHC) condition. The fluid biomarkers are obtained from a publicly available dataset for diabetic (N=105) and DHC (N=57) conditions. The features, such as systolic blood pressure, fasting blood glucose, diastolic blood pressure, and total cholesterol are extracted and statistically analyzed. Data balancing technique namely synthetic minority oversampling technique is applied on the minority class to balance the dataset. Machine learning techniques namely, linear discriminant analysis, random forest, K-nearest neighbor, and linear support vector machine are used to perform the classification between the two groups. The results show that systolic blood pressure, diastolic blood pressure, and total cholesterol are elevated in the comorbid condition. These features also exhibit a statistical significance (p<0.001) between the two groups. This study also addresses the data imbalance issue, which is resolved by using an oversampling technique to mitigate the bias resulting from imbalanced data. The LDA classifier achieves a maximum accuracy of 61.2% in distinguishing between the two conditions. Machine learning based approaches may help in the prediction of comorbid conditions. This can act as a guideline for future studies on the progression of diseases and the identification of fluid biomarkers.

A Comparative Evaluation of Micro-Leakage in Fiber Post Luted and Core Buildup Performed with Two Different Resin Cements: An In vitro Study.

Objective: To compare the micro-leakages of fiber post luted and core buildup performed with ParaCore (Coltene) and LuxaCore (DMG) resin cement. Materials and Methods: Thirty-six single-rooted teeth were selected and treated with root canal treatment and fiber post cementation with two types of resin cement (LuxaCore and ParaCore). Samples were exposed to 500 cycles of thermocycling, immersed in 2% methylene dye and centrifuged and sectioned longitudinally, and checked under a stereomicroscope. Results: LuxaCore and ParaCore showed a mean of 0.39250 mm and 0.47500 mm micro-leakage, respectively. Conclusion: There was a statistically non-significant difference seen with group 3 (LuxaCore) versus group 4 (ParaCore) (P > 0.05).

Percutaneous Pigtail Catheter Drainage of Spontaneous Intestinal Perforation in Premature Infants.

INTRODUCTION: Peritoneal drainage is an established management strategy for spontaneous intestinal perforation (SIP) in premature infants. We sought to evaluate the safety and efficacy of percutaneous pigtail catheter placement as an alternative to drain insertion via a lower quadrant incision. METHODS: Patients less than 32 weeks gestational age who underwent peritoneal drain placement for SIP at two neonatal intensive care units between 2011 and 2022 were identified. Incisional drainage (ID) or percutaneous pigtail catheter drainage (PD) was used based upon the usual practices of the surgeons. ID (n = 19) was performed via a 5-mm right lower quadrant incision into which a one-fourth-inch Penrose or red rubber catheter was placed. PD (n = 18) was accomplished using a Seldinger technique by which a 6.0 or 8.5 F pigtail catheter was passed through the left lower quadrant. Demographics and physiological parameters at the time of drainage were recorded and short-term and long-term outcomes were evaluated. RESULTS: Thirty seven infants were identified. There were no differences in demographics or physiological derangement between the groups. Patients who underwent ID had more frequent stool drainage, a greater transfusion requirement, and a longer time to full feedings (60.6 v 37.7 d, P = 0.04). Incisional hernias (n = 3, 16%) only developed after ID. The duration of drain placement, length of stay, and time to resolution of pneumoperitoneum were similar with ID and PD as was the incidence of premature drain dislodgement and subsequent laparotomy. CONCLUSIONS: Percutaneous drain placement provided effective drainage in infants with SIP and was associated with more rapid feeding advancement and no incidence of incisional hernia.

A Method to Predict Comorbid Conditions Using Risk Factor Profile of Multiple Fluid Biomarkers.

The co-occurrence of diabetes, hypertension, and cardiovascular diseases together can make clinical management and treatment more complex. Early detection of comorbid conditions can help in creating personalized treatment plans. Multiple fluid biomarkers can be used to enhance the diagnostic accuracy of identifying comorbidity. This study aims to distinguish non-comorbid and comorbid conditions using the risk factor profile of multiple fluid biomarkers, such as creatine phosphokinase, platelet count, serum creatinine, and ejection fraction. Area feature is computed by utilizing risk factor profile of the biomarkers, and a random forest classifier is used to distinguish the two conditions. The results indicate that the area of the radar plot is more significant for differentiating comorbid from non-comorbid conditions. RF classifier achieves the highest accuracy of 59.91% to differentiate the two conditions. Thus, multiple fluid biomarkers could be used to accurately detect the comorbid condition and improve the treatment plan individually.

SARS-CoV-2 severity classification from plasma sample using confocal Raman spectroscopy.

The world is on the brink of facing coronavirus's (COVID-19) fourth wave as the mutant forms of viruses are escaping neutralizing antibodies in spite of being vaccinated. As we have already witnessed that it has encumbered our health system, with hospitals swamped with infected patients observed during the viral outbreak. Rapid triage of patients infected with SARS-CoV-2 is required during hospitalization to prioritize and provide the best point of care. Traditional diagnostics techniques such as RT-PCR and clinical parameters such as symptoms, comorbidities, sex and age are not enough to identify the severity of patients. Here, we investigated the potential of confocal Raman microspectroscopy as a powerful tool to generate an expeditious blood-based test for the classification of COVID-19 disease severity using 65 patients plasma samples from cohorts infected with SARS-CoV-2. We designed an easy manageable blood test where we used a small volume (8 µl) of inactivated whole plasma samples from infected patients without any extra solvent usage in plasma processing. Raman spectra of plasma samples were acquired and multivariate exploratory analysis PC-LDA (principal component based linear discriminant analysis) was used to build a model, which segregated the severe from the non-severe COVID-19 group with a sensitivity of 83.87%, specificity of 70.60% and classification efficiency of 76.92%. Among the bands expressed in both the cohorts, the study led to the identification of Raman fingerprint regions corresponding to lipids (1661, 1742), proteins amide I and amide III (1555, 1247), proteins (Phe) (1006, 1034), and nucleic acids (760) to be differentially expressed in severe COVID-19 patient's samples. In summary, the current study exhibits the potential of confocal Raman to generate simple, rapid, and less expensive blood tests to triage the severity of patients infected with SARS-CoV-2.

Unraveling the Secrets of Colistin Resistance with Label-Free Raman Spectroscopy.

The rise in number of infections from multidrug-resistant (MDR) Gram-negative microbes has led to an increase in the use of a variety of 'polymyxins' such as colistin. Even though colistin is known to cause minor nephro- and neuro-toxicity, it is still considered as last resort antibiotic for treating MDR infections. In this study, we have applied Raman spectroscopy to understand the differences among colistin sensitive and resistant bacterial strains at community level. We have successfully generated colistin resistant clones and verified the presence of resistance-causing MCR-1 plasmid. A unique spectral profile associated with specific drug concentration has been obtained. Successful delineation between resistant and sensitive cells has also been achieved via principal component analysis. Overall findings support the prospective utility of Raman spectroscopy in identifying anti-microbial resistance.

Metabolomics Profiling of Pituitary Adenomas by Raman Spectroscopy, Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy, and Mass Spectrometry of Serum Samples.

To date, no studies are available in which pituitary adenomas (PAs) have been studied using techniques like confocal Raman spectroscopy, attenuated total reflection-Fourier transform infrared (FT-IR), and liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the same serum samples. To understand the metabolomics fingerprint, Raman spectra of 16 acromegaly, 19 Cushing's, and 33 nonfunctional PA (NFPA) and ATR-FTIR spectral acquisition of 16 acromegaly, 18 Cushing's, and 22 NFPA patient's serum samples were acquired. Next, Principal component-based linear discriminant analysis (PC-LDA) models were developed, Raman spectral analysis classified acromegaly with an accuracy of 79.17%, sensitivity of 75%, and specificity of 81.25%, Cushing's with an accuracy of 66.67%, sensitivity of 100%, and specificity of 52.63%, and NFPA with an accuracy of 73.17%, sensitivity of 75%, and specificity of 72.73%. ATR-FTIR spectral analysis classified acromegaly with an accuracy of 95.83%, sensitivity of 100%, and specificity of 93.75%, Cushing's with an accuracy of 65.38%, sensitivity of 87.5%, and specificity of 55.56%, and NFPA with an accuracy of 70%, sensitivity of 87.5%, and specificity of 43.75%. In either of the cases, healthy individual cohorts were clearly segregated from the disease cohort, which identified differential regulated regions of nucleic acids, lipids, amides, phosphates, and polysaccharide/C-C residue α helix regions. Furthermore, LC-MS/MS-based analysis of sera samples resulted in the identification of various sphingosine, lipids, acylcarnitines, amino acids, ethanolamine, choline, and their derivatives that differentially regulated in each tumor cohort. We believe cues obtained from the study may be used to generate the metabolite-based test to diagnose PAs from serum in addition to conventional techniques and also to understand disease biology for better disease management, point of care, and improving quality of life in PA patients.

Growth Kinetics Monitoring of Gram-Negative Pathogenic Microbes Using Raman Spectroscopy.

Optical density based measurements are routinely performed to monitor the growth of microbes. These measurements solely depend upon the number of cells and do not provide any information about the changes in the biochemical milieu or biological status. An objective information about these parameters is essential for evaluation of novel therapies and for maximizing the metabolite production. In the present study, we have applied Raman spectroscopy to monitor growth kinetics of three different pathogenic Gram-negative microbes Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii. Spectral measurements were performed under 532 nm excitation with 5 seconds of exposure time. Spectral features suggest temporal changes in the "peptide" and "nucleic acid" content of cells under different growth stages. Using principal component analysis (PCA), successful discrimination between growth phases was also achieved. Overall, the findings are supportive of the prospective adoption of Raman based approaches for monitoring microbial growth.

Impact of SARS-CoV-2 on multiple gestation pregnancy.

OBJECTIVE: To assess clinical presentations, pregnancy complications, and maternal and neonatal outcomes among women with multiple gestation pregnancy (MGP) and confirmed SARS-CoV-2 (COVID-19) infection and to compare the data with a pre-pandemic period. METHODS: A retrospective study at a dedicated COVID-19 Hospital in Mumbai, India. Data were obtained from the PregCovid Registry of pregnant and postpartum women with PCR-confirmed SARS-CoV-2 infection from April to September, 2020. Data were also compared with a cohort of women with MGP attending the hospital pre-pandemic (n = 63). RESULTS: Data from 879 women (singleton pregnancy, n = 859; MGP, n = 20) with COVID-19 were assessed. The twinning rate was 34.2 per 1000 births. As compared with singleton pregnancies, a higher proportion of women with MGP and Covid-19 delivered preterm (P = 0.001). Spontaneous abortions were also higher in the MGP group than in the singleton group (P = 0.055). The incidence of pre-eclampsia/eclampsia was higher in the COVID-19 MGP group than in both the COVID-19 singleton (41.6% vs. 7.9%) and pre-pandemic MGP (50.0% vs. 12.7%) groups. CONCLUSION: There was a higher risk of pre-eclampsia among women with MGP and COVID-19. Women with MGP and COVID-19 infection should receive special attention with a multidisciplinary approach to both maternal and neonatal care during the pandemic.

Efficacy of Dietary Supplements in Inflammatory Bowel Disease and Related Autoimmune Diseases.

The microbiome is an important contributor to a variety of fundamental aspects of human health, including host metabolism, infection, and the immune response. Gut dysbiosis has been identified as a contributor to the errant immune response in a variety of immune-mediated inflammatory diseases (IMIDs), such as inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and psoriatic disease (psoriasis and psoriatic arthritis). Given this, probiotics and prebiotics have been investigated as therapeutic options in these disease states. In our review, we highlight the current evidence on prebiotics and probiotics as well as other supplements (such as fish oils, vitamin D, and curcumin) as therapies for IBD. Recommendations, however, regarding the specific use of such supplements in IBD have been lacking, particularly from professional societies, often due to study limitations related to small sample sizes and design heterogeneity. Hence, we additionally examine the literature on the use of prebiotics, probiotics, and other supplements in related IMIDs, namely RA and psoriasis/psoriatic arthritis, as these diseases share many approved therapeutic options with IBD. Based on these combined findings, we offer additional evidence that may help guide clinicians in their treatment of patients with IBD (and other IMIDs) and provide recommendations on potential next steps in therapeutic research in this area.

Cocos nucifera and metformin combination for modulation of diabetic symptoms in streptozotocin induced diabetic rats.

BACKGROUND: Cocos nucifera, belonging to Arecaceae family, holds quite an importance in the Indian traditional medicinal system. C.nucifera inflorescence (CnI) has been reported in the literature to be useful in the treatment of diarrhoea, dysentery, diabetes, and dyspepsia. In this study, we aimed to evaluate the efficacy of CnI as an adjuvant with metformin in ameliorating Type-2 diabetes mellitus (T2-DM). OBJECTIVES: To evaluate antidiabetic activity of CnI in combination with metformin in Streptozotocin (STZ) induced diabetic rats. MATERIALS AND METHODS: Diabetes was induced in male Wistar rats using streptozotocin (45 mg/kg; i.p.). Plasma glucose level (PGL) was estimated after 72 h of STZ injection. Ethanolic extract of CnI (250 mg/kg and 500 mg/kg) per se and in combination with metformin (22.5 mg/kg) was administered orally once daily to rats for a period of 28 days. PGL level was estimated on 7th, 14th and 21st day followed by Oral Glucose Tolerance Test (OGTT) and PGL both on the 28th day of treatment. DPPH assay was performed to evaluate antioxidant activity of CnI extract. RESULTS: Extract of CnI (250 mg/kg and 500 mg/kg alone and the combination of extract (250 mg/kg) along with metformin (22.5 mg/kg) significantly decreased PGL (p < 0.0001) on 7th, 14th, 21st and 28th days. Histopathological analysis of pancreatic tissue showed that treatment with CnI extract per se and in combination with metformin improved the damaged architecture of pancreas. CONCLUSION: The combination therapy of CnI and metformin produced a significant antidiabetic effect than that of the extract alone and provides a scientific rationale for their use in antidiabetic therapy as an adjuvant.

A nutraceutical combination of Cinnamomum cassia &Nigella sativa for Type 1 diabetes mellitus.

BACKGROUND: Nigella sativa (black cumin) and Cinnamomum cassia (Cinnamon) are an integral part of the Indian diet, and have also been sourced in the ayurveda, the traditional Indian system of medicine, for their medicinal properties. Both the herbs individually have been successfully evaluated for their preliminary antidiabetic potential. OBJECTIVE: Herein, we dived deeper into antidiabetic properties of these herbs, by investigating the combinatorial effect of both herbs, on parameters of diabetes and further, as an adjunct to metformin therapy, for assessing the pharmacodynamics of herb-drug interaction in diabetes mellitus. The objectives were to screen the combinatorial extract of Nigella sativa & Cinnamomum cassia's (NSCCe) alone and in combination with metformin for its potential in mitigating symptoms of diabetes mellitus-alone, and as an adjunct therapy with metformin. MATERIALS AND METHODS: Diabetes was induced in the animals by a single intraperitoneal injection of streptozotocin. Animals were divided into seven groups with 6 animals each: Vehicle control, Negative control, Positive control (Metformin 50 mg/kg), treatment groups 4 and 5 received NSCCe at the doses of 100 mg/kg and 200 mg/kg, respectively. Groups 6 and 7 received the same doses, in combination with Metformin (50 and 25 mg/kg). Following a 28-day dosing period, plasma glucose levels, lipid profile and renal function profile were evaluated. Histopathological examinations were performed to measure any morphological change in kidney, liver and pancreatic tissue. RESULTS: Combination of Nigella sativa & Cinnamomum cassia extracts significantly normalized plasma glucose levels, lipid profile and kidney function parameters, compared to the diabetic control group. Animals treated with the combinatorial extract and metformin showed more prominent effects on these parameters. Significant reversal in the pancreatic cell damage was observed on treatment with NSCCe. CONCLUSION: This study generates evidence to support Nigella sativa & Cinnamomum cassia as an adjunctive in diabetes treatment protocols.

Hospital time prior to death and pancreas histopathology: implications for future studies.

AIMS/HYPOTHESIS: Diabetes research studies routinely rely upon the use of tissue samples from human organ donors. It remains unclear whether the length of hospital stay prior to organ donation affects the presence of cells infiltrating the pancreas or the frequency of replicating beta cells. METHODS: To address this, 39 organ donors without diabetes were matched for age, sex, BMI and ethnicity in groups of three. Within each group, donors varied by length of hospital stay immediately prior to organ donation (<3 days, 3 to <6 days, or ≥6 days). Serial sections from tissue blocks in the pancreas head, body and tail regions were immunohistochemically double stained for insulin and CD45, CD68, or Ki67. Slides were electronically scanned and quantitatively analysed for cell positivity. RESULTS: No differences in CD45+, CD68+, insulin+, Ki67+ or Ki67+/insulin+ cell frequencies were found when donors were grouped according to duration of hospital stay. Likewise, no interactions were observed between hospitalisation group and pancreas region, age, or both; however, with Ki67 staining, cell frequencies were greater in the body vs the tail region of the pancreas (∆ 0.65 [unadjusted 95% CI 0.25, 1.04]; p = 0.002) from donors <12 year of age. Interestingly, frequencies were less in the body vs tail region of the pancreas for both CD45+ cells (∆ -0.91 [95% CI -1.71, -0.10]; p = 0.024) and insulin+ cells (∆ -0.72 [95% CI -1.10, -0.34]; p < 0.001). CONCLUSIONS/INTERPRETATION: This study suggests that immune or replicating beta cell frequencies are not affected by the length of hospital stay prior to donor death in pancreases used for research. DATA AVAILABILITY: All referenced macros (adopted and developed), calculations, programming code and numerical dataset files (including individual-level donor data) are freely available on GitHub through Zenodo at https://doi.org/10.5281/zenodo.1034422.